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Solutions Consulting Manager in San Francisco

145 active opportunities · Updated October 2026

Explore current solutions consulting manager jobs in San Francisco. Filter by work mode, employment type, experience, department, date posted and distance.

DU
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $1.3M/yr

Quick readStrong listing-quality and freshness signals

About the Team We help Merchants access the financial products they need to grow and operate their businesses. DoorDash Capital is one of the company's fastest-growing bets, and our team owns the full growth engine from identifying unmet Merchant needs to launching products and scaling them. We obsess over how to deliver more value to Merchants through our platform and our financing partnerships, and we measure ourselves on adoption, revenue, and Merchant outcomes. About the Role You will report to the Director, S&O New Business on our DoorDash Capital team and own the growth of one of our newest bets with a key partner in the financing space. This is a 0-to-1 growth role: you'll take an early product and scale it to maturity by driving adoption, conversion, and revenue. You will have support from product, engineering, sales, and marketing. The ideal candidate is energized by finding growth levers, moving fast, running experiments, and learning from data in a high-velocity environment. You’re excited about this opportunity because you will… Strategize – Understand the needs of our Merchants, prioritize those needs by impact, and create solutions with cross-functional partners Build – Drive the implementation of new product features and processes for managing Merchant financial products Construct - Navigate in an ambiguous environment and bring structure to undefined opportunities. There won’t be playbooks or templates, instead you will create them. Analyze – Leverage data whenever possible to inform your hypothesis and convince cross functional partners. Influence – Work cross-functionally with our Product, Engineering, Sales, Marketing, Finance, and Business Development teams to align on a path forward and bring these products to market We’re excited about you because… You have 4+ years of experience in strategy & operations / product management / investment banking / management consulting / mergers & acquisitions or relate

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DU
📍 San Francisco, Canada
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About the Team The Finance & Strategy team accelerates the growth of our business by identifying and implementing new opportunities and solutions. We partner with teams across the company to improve the profitability, scalability and defensibility of our business model. We're looking for people who can use strategy to identify areas of opportunity, and collaborate to help carry projects from conception through execution. About the Role We are looking for a Finance Manager who will work with partners across DoorDash to ensure we are making the most efficient investment and capital allocation decisions while improving the experience for our merchants and other marketplace participants. You will help lead financial reporting, forecasting, and planning, and will guide financial insights and direction for all of our operational decisions and strategies. You’re excited about this opportunity because you will… Conduct weekly reporting of financial performance of DoorDash’s Merchant business, forecast key financial metrics based on quantitative analysis of historical data.Support quarterly financial planning, collaborate with cross functional business partners to identify growth areas and business priorities.Deep-dive into complex operational questions and collaborate cross-functionally outside Finance (Sales, Operations, Support) as well as within Finance (Accounting, Analytics, BI) to uncover the most optimal data-driven business decisions and investments.Identify key opportunities & risks to the business, quantify and evaluate the impacts, propose a solution and investment case, and ensure efficient execution. Leverage and apply knowledge of SQL, finance, analytics, and technology to manage financial reporting, forecasting, and quantitative analysis to assist DoorDash in making better business decisions. We’re excited about you because… 6+ years of experience overall, preferably from Strategic Finance, Corporate Finance, Investment Banking, or Consulti

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📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $200K/yr

Quick readStrong listing-quality and freshness signals

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

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📍 San Francisco, Canada· Full-time
✓ High-confidence listing

$220K – $310K/yr

Quick readStrong listing-quality and freshness signals

About Glean: Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more - deeply embedded where people get things done. You’ll ship agentic capabilities on an open, extensible stack, with the craf

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SC
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $110K/yr

Quick readStrong listing-quality and freshness signals

The Sigma Commercial Solutions Engineer believes in the power of analytics to transform organizations and uncover new data insights to increase business agility. The Sigma Solutions Engineer will act as the trusted advisor to our prospects and customers working in tandem with Sales, Business Development, Product Management, Customer Success, and Support. This individual is ultimately responsible for managing and delivering on all activities related to the technical presales cycle. This includes presentations, demonstrations, and hands on development of prototypes. You will align closely with our Commercial Sales Representatives focused on sales in new and existing accounts. What You Will Be Doing Understand and uncover business challenges and issues faced by the customer and be able to run targeted discovery sessions or workshops Engage with business users to define, create, and showcase solution prototypes Build and present customized demos for customers, trade shows, and webinars Confidently present and articulate the business value of the Sigma platform to all levels within an organization Deliver product, technical, and security related responses to RFPs/RFIs Participate in product, sales, and relevant technology certifications to acquire, maintain, and grow skill sets Work as a team player by contributing, learning, and sharing new knowledge Be conversant in integration and data migration approaches to help customers develop their data lifecycle and analytics strategy with Sigma Manage multiple customer engagements concurrently Attain quarterly and annual objectives assigned by management Become a Sigma champion and product expert; prospects and customers will look to you for advice and expertise Qualifications We Need Minimum 2 years of analytics, business intelligence, or sales engineering experience Customer relationship skills Strong understanding of database concepts Understanding of advanced spreadsheet concepts Cloud

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SC
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

$135K – $180K/yr

Quick readStrong listing-quality and freshness signals

Solution Architect Sigma Computing The SA role has evolved. Here’s the version we’re hiring for. The SA job in 2026 is not the SA job in 2023. Three things now sit at the center of how we evaluate this role. This hire has to do all three at a senior level, with the architectural depth to back it up. 1. Use AI every day to do the job better. If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are. We expect this hire to treat AI tooling as default infrastructure, not novelty. Come with a point of view on what you run, why, and how you use it to compress weeks of work into days. 2. Sell AI into the account. Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what. You have to be fluent. You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns. You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call. You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs. 3. Sell against AI. Every enterprise deal has AI competition in it. Sometimes it is Databricks Genie. Sometimes it is Snowflake Cortex Analyst. Sometimes it is a systems integrator pitching a bespoke agent built over the weekend. You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving. You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls. About Sigma Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, an

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📍 San Francisco, Canada
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

POSITION SUMMARY: A Phlebotomist serves patients by identifying the best method for retrieving blood; preparing specimens for laboratory testing; and performing screening procedures. The Phlebotomist will also act as an operations manager for the designated patient service center (PSC) and oversee Natera’s phlebotomy program at the specified location. Depending upon growth opportunities, this role may also require oversight of other phlebotomists as needed to support patient volume growth. *** IF YOUR STATE REQUIRES A PHLEBOTOMY LICENSE, IT MUST BE SENT IN WITH YOUR RESUME WITH YOUR APPLICATION *** PRIMARY RESPONSIBILITIES: Verifies test requisitions by comparing information with orders and requisition documentation; brings discrepancies to the attention of Natera product management leadership. Verifies patient by reading patient identification. Obtains blood specimens by performing venipunctures and finger sticks. Maintains specimen integrity by using aseptic technique, following Natera[KC1] procedures; observes isolation procedures. Tracks collected specimens by initialing, dating, and noting times of collection; maintaining daily tallies of collections performed[MB2] in Natera provided system. Maintains quality results by following Natera procedures and testing schedule; recording results in the quality-control log; identifying and reporting needed changes reporting KPIs to product management leadership on biweekly basis. Maintains safe, secure, and healthy work environment by following standards and procedures; complies with legal regulations. Resolves unusual test orders by contacting the physician, pathologist, nursing station, or reference laboratory; referring unresolved orders back to the originator for further clarification; notifying internal Natera team [MB3] of unresolved orders. Updates job knowledge by participating in educational opportunities; reading professional publications; main

DU
📍 San Francisco, Canada
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About the Team DoorDash Labs is an independent team within DoorDash. We're hiring a backend software engineer to work at the intersection of software engineering and robotics to solve key business problems with elegant technical solutions. If you have a passion for applying robotics solutions to a service loved by millions of people, then we want to talk to you! About the Role We’re looking for Backend Engineers to work on both Product and Product Platform based teams in DoorDash Labs. Product focused Engineers work at the intersection of product and infrastructure to solve key business problems with elegant technical solutions. You'll operate our backend services and architecture that support all product functionality and will be challenged to consider the big picture -- collaborating cross-functionally, as well as evaluating and executing on trade-offs to maximize business impact for the company. You're excited about this opportunity because you will... Design and implement backend services for IoT that integrates with core DoorDash data, focused on reliability, and future extensibility Create a well documented APIs for other departments to integrate with Improve performance, reliability, scalability and security for our backend systems Introduce tools and best practices to accelerate our development process Design and implement backend services for autonomous delivery system that integrate with core DoorDash data. We're excited about you because you have... B.S., M.S., or PhD. in Computer Science or equivalent 6+ years of industry experience as a software engineer Experience with backend for frontend architecture Ability to improve efficiency, scalability, and stability of multiple system resources Experience with service oriented architecture, writing REST API’s, unit testing, and architectural design Understanding of modern web stacks and architecture (HTTP, REST) Experience with SQL Experience with either Java or Kotlin Nice to Have Experience with

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DU
📍 San Francisco, Canada
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role We are hiring an Autonomy Platform Engineer to build and evolve the foundational software that runs our autonomy stack across robot and compute platforms. The Autonomy Platform team works across embedded Linux, compute and sensor enablement, robotics middleware, process orchestration, data capture and replay, system observability, and performance. You will develop production software and tooling that enables autonomy engineers to bring up new hardware, deploy services reliably, diagnose failures, and validate system performance across robot generations. You will work closely with autonomy, firmware, electrical, hardware, manufacturing, and validation engineers and report to the Autonomy Platform Lead. We expect this role to be hybrid with some time in-office and some time remote. You’re excited about this opportunity because you will… Build and maintain core runtime, middleware, and platform services used by autonomy applications. Enable new compute, camera, lidar, and other sensor platforms. Improve process orchestration, messaging, configuration, startup and shutdown behavior, resource isolation, and fault recovery. Develop system observability, tracing, performance measurement, diagnostics, and regression-detection capabilities. Build reliable data capture, replay, and debugging workflows. Create provisioning, packaging, deployment, integration-test, and platform-readiness tooling. Lead complex debugging across application, middleware, OS, driver, networking, timing, and hardware boundaries. We’re excited about you because… Strong production C++ and Python experience. Experience with embedded Linux, robotics, autonomous vehicles, or complex mechatronic systems. Solid u

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SC
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

$175K – $210K/yr

Quick readStrong listing-quality and freshness signals

As Sigma scales its global footprint, the Sales Engineering (SE) organization is the technical engine driving our GTM motion. We are looking for a Strategy and Operations Lead, SE to partner directly with our VP of SE and serve as the operational bedrock for this critical organization. Operating within our broader GTM Strategy & Operations team, you will own the global operating rhythm, operational infrastructure, and capacity planning for the entire SE organization. You will drive strategy across a highly matrixed, global environment. You are part strategist, part builder, and part operator - responsible for ensuring our pre-sales motion scales seamlessly. What You Will Do Drive Business Reporting & the SE Operating Rhythm: Own the cadence of the SE organization. Design and execute regular business reviews and leverage Sigma to build robust, real-time reporting that gives the VP of SE crystal-clear visibility into technical pipeline health, team utilization, and conversion metrics. Optimize Funnel Mechanics & Deal Acceleration: Deep dive into the pre-sales funnel to identify where deals stall during technical validation. Partner with SE leadership to optimize the Proof of Concept (POC) lifecycle, remove friction, and accelerate the technical win. Lead Global Headcount & Capacity Planning: Serve as the SE representative in cross-functional GTM planning cycles. Own end-to-end global SE capacity requirements, design territory allocation frameworks, and manage annual headcount planning seamlessly across AMER, EMEA, and APAC. Build Solutions in Sigma: Leverage Sigma itself to build robust operational solutions, designing the dashboards, data models, and workflows needed for POC tracking, capacity management, and performance visibility. Act as the Cross-Functional Hub: Represent the SE organization in all major GTM Strategy & Operations initiatives. Serve as the connective tissue between SE, Sales, Product, and RevOps, ensuring SE requir

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SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $252K/yr

Quick readStrong listing-quality and freshness signals

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Forward Deployed AI Engineering Manager on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, lead a team that architects specific AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a Management role that combines deep engineering and AI expertise, leading a team, and working on customer-facing problems. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineeri

PythonAWSAzureGCP
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $216K/yr

Quick readStrong listing-quality and freshness signals

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. About our Customer Platform team: Our Customer Platform Team plays a pivotal role in integrating our platform with external systems and ensuring seamless, reliable connectivity for both internal users and customers. As the leader of this team, you’ll drive the strategy, architecture, and development of our connectivity solutions, focusing on API integration, distributed systems, and a robust data platform. Your role will be crucial in maintaining and enhancing our platform’s ability to meet the needs of both our internal and external stakeholders. Responsibilities: Own large areas within our product Comfortable working cross functionally, whether that be internal or external customers Build features end-to-end: front-end, back-end, system design, debugging and testing Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Influence the culture, values, and processes of a growing engineering team Inspire and mentor less experienced engineers Collaborating with cross-functional teams to define, design, and ship new product features and experiences. Requirements: At least 7-10 years of relevant experience is preferred Track record of shipping high-quality products and features at scale Desire to work in a very fast-paced environment Abil

AWSRestAIGo
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $288K/yr

Quick readStrong listing-quality and freshness signals

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. Role Overview As a Senior Staff Frontier Agents Engineer on our Enterprise team, you'll be the technical bridge between Scale AI's cutting-edge AI capabilities and our most strategic customers. You'll work with enterprise clients to understand their unique challenges, architect custom AI solutions, and ensure successful deployment and adoption of AI systems in production environments. This is a hands-on technical role that combines deep engineering expertise with customer-facing problem solving. You'll work directly with customer engineering teams to integrate AI into their critical workflows. Key Responsibilities Customer Integration & Deployment Partner directly with enterprise customers to understand their technical infrastructure, data pipelines, and business requirements Design and implement custom integrations between Scale AI's platform and customer data environments (cloud platforms, data warehouses, internal APIs) Build robust data connectors and ETL pipelines to ingest, process, and prepare customer data for AI workflows Deploy and configure AI models and agents within customer security and compliance boundaries AI Agent Development Develop production-grade AI agents tailored to customer use cases across domains like customer support, data analysis, content generation, and workflow automation Architect multi-agent systems that orchestrate between different models, tools, and data sources Implement evaluation frameworks to measure agent performance and iterate toward business objectives Design human-in-the-loop workflows and feedback mechanisms for continuous agent improvement Prompt Engineering & Optimization Create sophisticate

PythonAWSAzureGCP
SA
📍 San Francisco, Canada· Full-time
✓ High-confidence listing

From $264.8K/yr

Quick readStrong listing-quality and freshness signals

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

PythonAWSRestMachine Learning
DU
📍 San Francisco, Canada· Full-time
✓ High-confidence listing
Quick readStrong listing-quality and freshness signals

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing pipelines, data structures, and data warehouse architectures; this team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Softare Engineer II to be a technical powerhouse to help us scale our data infrastructure, automation and tools to meet growing business needs. You're excited about this opportunity because you will… Work with business partners and stakeholders to understand data requirements Work with engineering, product teams and 3rd parties to collect required data Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Develop and implement data quality checks, conduct QA and implement monitoring routines Improve the reliability and scalability of our ETL processes Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We're excited about you because… 3+ years of professional experience working in data engineering, business intelligence, or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Proficiency in programming languages such as Python/Java 3+ years of experience in ETL orchestration and workflow management tools like Airflow, Flink, Oozie and Azkaban using AWS/GCP Expert in Database fundamentals, SQL and distributed computing 3+ years of experience with the Distributed data/similar ecosystem (Spark, Hive, Druid, Presto) and streaming technologies such as Kafka/Flink. Experience working with Snowflake, Redshift, PostgreSQL and/or other DBMS

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