Analytics Systems Director Jobs

SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars. SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next. ABOUT THE ROLE: We are seeking a skilled Analytics Engineer to build and maintain robust data systems that enable high-impact quantitative analysis and business decision-making. This role combines strong software engineering practices with expertise in large-scale data processing and advanced analytical methods to deliver reliable, scalable solutions across the organization. This is an opportunity to work on mission-critical systems that power quantitative decision-making at global scale. RESPONSIBILITIES: Design, implement, and optimize end-to-end data pipelines for processing high-volume datasets using tools such as Spark, Kafka, Flink, etc. Develop quantitative models and statistical frameworks to support experimentation, forecasting, and performance measurement. Build and maintain data infrastructure that ensures data quality, consistency, and accessibility for analytical workflows. Collaborate with product engineering, product, and operations teams to translate business requirements into production-grade data systems and insights. Conduct A/B tests, causal analysis, and performance evaluations to drive measurable improvements in key metrics. Implement monitoring, alert

About Us Pearl is AI for professional services at global scale, combining advanced AI with verified human expertise to deliver help that is accurate, accountable, and fast. Since 2003, our network has connected millions of customers with licensed professionals across 196 countries, making real expertise available anytime, anywhere. Our Values Data driven: Start with truth, measure what matters. Courageous: Bias to action; run toward hard problems. Innovative: Seek novel, elegant solutions. Lean: Do more with less. Build, ship, learn fast. Humble: Strong opinions, lightly held. About the Role Analytics is moving beyond dashboards. We’re building intelligent systems that let analysts and business users explore data, automate analysis, design scalable architectures, and get insights faster and we need a senior engineer to build the data foundations and AI-powered tools that make that possible. This is a hands-on builder role at the intersection of analytics engineering and applied AI. You'll own the pipelines, datasets, and metrics that the business runs on, and you'll build the LLM-powered applications, copilots, agents, natural-language data experiences that sit on top of them. You'll work directly with product, growth, and business teams on real B2C and customer data. What You’ll Do Analytics Engineering & Business Analytics Build and own scalable data pipelines, transformations, analytical datasets, and reusable data products using SQL and Python. Analyze B2C, product, and customer data to identify trends, performance drivers, and actionable insights. Translate business and product questions into reliable metrics and decision-support solutions that help teams measure performance and understand customer behavior. AI-Powered Analytics Design, build, and deploy LLM-powered applications, agents, and analytics workflows using RAG, tool calling, MCP, and modern agent frameworks. Develop reusable AI tools that enable analysts and business user

At Affirm, we exist for the moments that matter—giving people a clear, predictable way to pay over time, with no hidden fees, no surprises, and no tradeoffs on what matters most. We’re looking for a curious, driven professional to join our Revenue Analytics team. This builds and owns the data products, reporting infrastructure, semantic foundations, and analytical systems that power Affirm’s Revenue organization. As a Senior Analyst, Revenue Analytics, you’ll build scalable data products that power day-to-day decision-making - owning end-to-end work across data modeling, metric definitions, dashboards, automation, and enablement. You’ll also help strengthen our semantic layer and data governance, laying the foundation for reliable AI. The ideal candidate combines strong technical and analytical skills with the ability to turn ambiguous business questions into durable, well-tested data infrastructure. What you'll do Develop dbt data models, dashboards, metrics, and automation processes for the revenue field team and revenue analysts Build and maintain critical reporting data models that power external merchant reporting Build the semantic, metadata, and context layers that allow AI systems to accurately understand Revenue data, metrics, and business definitions Partner with Business Systems, engineering, and business stakeholders to translate requirements into durable, well-tested data products Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows) Develop processes, governance, and foundations to scale the impact of analytics within Revenue. What we look for 3+ years of work experience in an analytics engineering or business intelligence role Strong working knowledge of SQL, dbt, Python, data modeling, and data visualization Hands-on experience with BI tools (Sigma/Looker/Tableau), Databricks, and cloud data warehouses (Snowflake) Understanding of the data f

Zoox is seeking a high-agency, hands-on Lead Analytics Engineer to bridge the gap between our complex enterprise data sources and our AI-driven decision-making systems. You will lead the design and implementation of our semantic layer and data modeling strategy, ensuring that data from SAP (S/4HANA, Ariba, BRIM, ME), Workday, Salesforce, and Anaplan is transformed into clean, performant, and "AI-ready" datasets. This is a critical leadership role for a builder who wants to own the data foundation that powers our intelligent agents and business-wide analytical workflows. In this role, you will: Design and maintain a unified semantic model that provides a "single source of truth" for cross-functional stakeholders, AI Agents, Self Serve Analytics and Executive dashboards. Collaborate with Data & AI Engineers to structure and optimize the data that allows to query enterprise knowledge with high accuracy and low latency. Establish organizational standards for data modeling, version control, testing, and documentation to ensure high data quality and system maintainability. Implement automated testing and observability frameworks that proactively identify data anomalies and "self-heal" pipelines, ensuring our data is always reliable for downstream consumption. Partner with cross-functional business leaders to translate complex operational requirements into high-impact, scalable data solutions. Qualifications: 10+ years in Data Engineering & Analytics, with extensive hands-on experience building a semantic framework using Python, SQL and modern orchestration frameworks (e.g. Airflow, Lakeflow, Argo). With at least 2+ years of hands-on experience deploying AI generated code. Extensive experience using modern data stacks (e.g. Snowflake/Databricks, Big Query) to build complex, enterprise-grade data models. Deep understanding of data structures within large-scale enterprise platf

Our Global Structure Deliveroo is now part of DoorDash, bringing together teams with even greater reach, scale, and ambition. Depending on your role, you may collaborate with teammates, systems, and leaders across DoorDash and Wolt. Together, we’re unlocking new possibilities as one global team. Join us in our mission to transform the way people shop and eat, where impact, innovation and growth drive everything we do. Our Engineering teams tackle complex technical challenges across a global, three-sided marketplace, building and scaling systems that serve millions of customers, riders and partners every day. From real-time logistics to resilient infrastructure and marketplace optimisation, we design, build and operate technology that powers Deliveroo’s growth at scale. We’re looking for a BI Engineer to join our London team. This role is based in our London office with a hybrid setup, typically 3 days in the office. Get to know our Engineering team — what drives us, how we work, and what you can expect. About the Team The Core BI team builds and operates the services, integrations and automation that power business intelligence across DoorDash, Deliveroo and Wolt. Our platforms help analysts, Analytics Engineers, Data Scientists, Software Engineers and business teams discover trusted data and make informed decisions at scale. We combine software engineering, platform ownership, and a strong user focus to make BI tooling reliable, secure, scalable and self-service. The team supports the current BI ecosystem while helping shape a more integrated experience across the DoorDash group. About the Role As a BI Engineer on the Core BI team, you will build and operate the models, systems and automation behind our BI platforms. This will include supporting our extensive user base on our current BI stack (primarily Looker and Sigma) while helping shape a single, more integrated BI platform across DoorDash, Deliveroo and Wolt. You will own problems from discovery

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary CVS Health is seeking a strategic, data-driven Manager, Business Analysis, Workforce Initiatives, Data & Analytics to lead workforce intelligence and analytics initiatives that support enterprise workforce planning, talent pipeline development, program effectiveness, and business decision making. This role is responsible for transforming Workforce Initiatives data into actionable business intelligence that improves participant outcomes, strengthens talent pipelines, drives operational efficiency, and informs enterprise workforce strategy. Sitting at the intersection of data analytics, business strategy, workforce planning, technology, and operational excellence, the Manager will convert complex data into meaningful insights that influence talent, operational, and organizational outcomes. The successful candidate will serve as the business owner for the Workforce Initiatives data ecosystem, ensuring data quality, governance, reporting consistency, and scalability across key platforms including Workday, Applicant Tracking Systems (ATS), LearningHub, Sophia, and other enterprise technologies. As a strategic partner to Workforce Initiatives leadership, Human Resources, Talent Acquisition, Operations, Finance, Information Technology, and external stakeholders, this leader will identify trends, uncover opportunities, measure program effecti

About Vercel: Vercel is the agentic infrastructure company, freeing people and agents to ship what's next. For more than a decade we've helped builders move from idea to production with speed, security, and exceptional developer experience. Now we're scaling our products for both agents and people to ship and run software, built in the open and trusted by OpenAI, PayPal, Ramp, Supreme, and millions of developers worldwide. About the Role: We're looking for a People Systems Manager, Workday to join our People team and build the foundation for how People technology operates at Vercel. We've recently implemented Workday as our system of record, and we're just getting started. As we expand its capabilities and build toward public company-ready operations, we need someone to own the architecture, security, business processes, and governance behind it. We're building a headless People technology experience, with Workday as the engine behind it, not a traditional HR technology stack. Employees and managers will initiate transactions, access their data, and navigate People processes directly from the tools they already use. You'll make that possible, working closely with integration engineers to connect Workday's security model and Business Process Framework to the experiences we're building. This is a hands-on IC role with real ownership over how Workday operates at Vercel. You'll set standards, make architectural decisions, and build systems that scale, reducing manual work, strengthening controls, and creating data our growing People analytics function can trust. If you’re based within a pre-determined commuting distance of one of our offices (SF, NY, London, or Berlin), the role includes in-office anchor days on Monday, Tuesday, and Friday. If you're located beyond that distance, the role is fully remote. For location-specific details, please connect with our recruiting team. What You Will Do: Own the configuration, security architecture, and Business Process Framework

Perplexity is AI for people who expect more. On the data team, that means building the systems that make our data reliable, understandable, and usable by both humans and AI. We're looking for an analytics engineer or data engineer who wants to build the foundation for an AI-native data organization. You'll design core data models, pipelines, semantic layers, data quality systems, governance practices, and warehouse workflows that power the entire company: helping teams make strategic decisions, operate the business, and move faster with trusted data. You'll also make sure those systems are secure, privacy-aware, and legible to AI agents, data scientists, and the rest of the company. This role is for someone who can operate at the boundary of analytics engineering, data engineering, data governance, and internal product. You care about dimensional modeling, dbt standards, cost-aware warehouse design, access controls, privacy, and the details that make data trustworthy. You also believe AI should make the data stack faster, easier to maintain, and more accessible across the company without weakening security or governance. What You'll Do Build the core data foundation - design and maintain high-quality data models, marts, and pipelines that make analysis fast, reliable, and reusable. Manage the data warehouse - help own warehouse architecture, environments, permissions, performance, cost, data lifecycle, and operational hygiene so the platform scales cleanly. Make the warehouse AI-readable - own the documentation, semantic context, metadata, lineage, and retrieval patterns that AI systems depend on to understand and query Perplexity's data correctly. Own data modeling standards - define and champion dbt patterns, dimensional modeling practices, naming conventions, tests, and review processes. Lead data governance practices - define standards for access, ownership, lineage, documentation, retention, quality, and sensitive data handling across the analytical warehouse.

The Team + The Role Pendo's People organization builds and supports the systems and processes that power the employee lifecycle. The team partners across People and Recruiting to ensure our HCM infrastructure runs smoothly and can scale with the company. As a Workday Systems Engineer, you'll own and evolve Workday as a core part of Pendo's HCM infrastructure. You'll manage configuration across key Workday modules, translate People and Recruiting requirements into scalable solutions, and maintain the reporting, security, integrations, and processes that keep the platform reliable. This role sits at the intersection of HR and technology, requiring a strong understanding of both People processes and the technical configuration behind them. This role is based in our Raleigh or New York City office. What this looks like day-to-day Workday platform ownership: Serve as the primary systems owner for Workday, managing configuration across HCM, Advanced Compensation, Time Tracking, and Time & Attendance. Maintain and evolve the platform as business needs change. People and Recruiting partnership: Partner directly with Recruiting and the broader People organization to understand business requirements and translate them into scalable Workday solutions. Balance stakeholder needs with sustainable system configuration. Open Enrollment: Lead or support annual Open Enrollment configuration, testing, and go-live activities. Help ensure Workday is configured and ready to support the enrollment process. Compensation cycles: Manage Workday setup for compensation cycles, including merit, bonus, and equity review processes. Support the configuration needed to run these programs effectively. System reliability and security: Troubleshoot Workday issues, manage security configurations, and maintain data integrity across integrations. Investigate problems and drive them through resolution. Reporting and analytics: Build and maintain reports, dashboards, and calculated fields that support

Autonomous vehicles have some of the largest, most complex software ever shipped in a safety-critical environment. Solving that problem is one of the most exciting technical challenges of our lifetime. As a Systems Test Engineer on our System Behavior Analysis Autonomous team, you will play a critical role in the development of Zoox's autonomous platform, working with a broad set of engineering teams across Zoox. You will help triage and root cause the issues identified during testing and real-world operations. You will also produce reports and insights that inform leadership on the overall quality and influence of engineering decisions. Your ability to distill complex systems and root cause issues will be crucial to producing a safe and stable vehicle platform. In this role, you will: Utilize data analytics to analyze and diagnose a wide range of system faults and errors related to perception, planner, and other AI software from both on-road testing and system simulations. Effectively categorize and prioritize issues based on severity, urgency, and potential impact on safety and performance by working collaboratively with cross-functional teams (engineering, software, testing). Identify trends in system failures and propose preventative measures to improve overall system safety and robustness by producing clear and concise reports of system issues, troubleshooting steps, and root cause analysis. Be hands-on, lead by example, and develop tools and workflows to drive improvements for both quality and quantity aspects of the triage. Demonstrate operational agility by quickly adapting to changing priorities, managing multiple tasks simultaneously, and implementing effective solutions in dynamic environments. Qualifications Bachelor's or Masters degree in Computer Science or STEM-related field Minimum of 5 years of experience in systems troubleshooting and diagnostics, preferably in the automotive or em

ABOUT THE ROLE: Accela is looking for an HR Technology & Analytics Specialist to provide hands-on support across HR systems, reporting, process improvement, AI-enabled efficiency, and data/document management. Reporting to the Principal, AI Enablement & HR Analytics, this role will support key HR technology projects and help maintain recurring reporting and HR systems activities during a temporary leave period. The ideal candidate is detail-oriented, comfortable working independently across multiple HR systems, and able to leverage technology and AI tools to simplify work and improve process efficiency. This is a 6-8 month contract position. SPECIFIC RESPONSIBILITIES: • Support Greenhouse and ADP reporting, system administration, and process improvements, including opportunities to automate or streamline existing workflows. • Run recurring and ad hoc reports from Greenhouse, ADP, and other HR systems and validate data for accuracy. • Leverage approved AI and automation tools to improve process efficiency, reporting, documentation, and recurring HR workflows. • Identify manual or repetitive processes and recommend practical opportunities for automation or AI-enabled improvement. • Update and reorganize HR SharePoint sites to improve content, structure, and usability. • Support migration of HR files and folders from Box to OneDrive/SharePoint, including file organization and validation. • Conduct audits of employee files and identify missing, incomplete, duplicate, or incorrectly stored documentation. • Maintain existing HR reports, dashboards, trackers, and recurring processes. • Troubleshoot routine HR system or data issues and document key processes to support continuity. • Partner with HR, Recruiting, IT, Finance, and other teams as needed. REQUIRED QUALIFICATIONS: • 3+ years of experience in HR technology, HRIS, HR

The Quant Trading team is responsible for trading and managing risks associated with different crypto products, including spots and derivatives. The team develops and implements trading strategies in fast-paced and complex trading environments. We are seeking an experienced Trading Analytics Developer to join our Quant Trading team and play a pivotal role in advancing our data and AI infrastructure. This role combines traditional quantitative development with cutting-edge AI platform engineering, focusing on building robust, scalable systems that serve both data analytics and artificial intelligence workloads. The ideal candidate will bridge the gap between high-performance trading systems and modern AI capabilities, ensuring reliability, performance, and actionable insights across both domains. Job Responsibilities Data Platform & Analytics Design, build, and operate high throughput batch and streaming data pipelines using Kafka, Flink, and ETL technologies Design and build unified analytics engine designed for processing large-scale data using Apache Spark and related tools Develop and optimize analytical data models for time-series, financial metrics, and trading activity Implement and manage analytical databases (ClickHouse, MongoDB, BigQuery, Snowflake, or similar) with cost-aware architecture Build idempotent data pipelines with robust backfill and reconciliation capabilities Create comprehensive monitoring for data quality, freshness, and pipeline reliability AI Platform Development Design, build, and operate internal AI platforms serving multiple trading teams Build reusable AI tooling including standardized RAG pipelines, prompt management, and self-service workflows Create and maintain agent systems using modern frameworks (LangGraph, A2A, MCP) with focus on controllability and auditability

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . This is a 12-week internship during summer 2027. You'll join the Analytics Engineering team within Platform, which builds and maintains the trusted data infrastructure that powers decision-making across Coinbase. As an Analytics Engineer Intern, you'll model complex data, build scalable pipelines, and deliver insights that help teams across the company unlock the full potential of our data. You will gain hands-on experience building production data systems at scale, mentorship from senior analytics engineers, and exposure to how data powers decision-making across a publicly traded crypto-native company. What you'll do: Build and maintain dimensional data models that transform raw data into clean, reliable datasets used by analysts, data scientists, and product teams across the organization. Develop data pipelines using SQL, ensuring data quality, freshness, and documentation meet production standards. Partner with cross-functional stakeholders to understand their data needs and deliver well-structured datasets or dashboards that enable self-serve analytics. Leverage generative AI tools to streamline data development, modeling, and documentation workflows. Investigate and resolve data quality issues, implementing tests and monitors that catch problems before they reach downstream consumers. Required Skills and Experience: Currently pursuing a degree in computer scienc

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Summary The O&M Gas Systems Engineer supports the safe, reliable, and efficient operation of bulk and specialty gas delivery systems that enable semiconductor manufacturing. This role partners with Operations, Maintenance, Manufacturing, Safety, and Engineering teams to improve system reliability, troubleshoot complex equipment issues, drive continuous improvement initiatives, and support capital and operational projects while ensuring compliance with environmental, health, safety, and quality standards. The engineer leverages data analytics, AI-enabled tools, and digital technologies to enhance decision-making, optimize system performance, and improve operational efficiency. Responsibilities Support the operation, maintenance, and continuous improvement of bulk and specialty gas systems to ensure safe and reliable semiconductor manufacturing operations. Analyze system performance data, identify improvement opportunities, troubleshoot equipment issues, and lead root cause investigations to improve reliability and reduce risk. Utilize AI, machine learning, and advanced analytics tools to identify trends, predict equipment failures, optimize maintenance strategies, and enhance operational performance. Develop and implement digital solutions, dashboards, automated reporting, and data visualization tools that improve engineering efficiency and decision-making. Ensure compliance with Micron safety, environmental, quality, and change management requirements while promoting a strong safety culture.</

At Linear, we're building the product development system for teams and agents. AI is fundamentally changing how software gets built, and we’re shaping the tools this new era requires. Founded in 2019, Linear has become the platform of choice for more than 40,000 companies (including OpenAI, Coinbase, and Ramp) to plan, build, and ship their products. Today, our team is distributed across North America, Europe, and Australia, and we’re continuing to grow internationally. What unites us is relentless focus, fast execution, and a deep care for software craftsmanship. The Data team works across Linear, supporting Product, Engineering, and GTM. We own our data pipelines, warehouse, dashboards, analysis, and integrations with third-party tools. As a small team, we focus on building systems that make data accessible and useful across Linear. We’re looking for someone who wants to help shape how we architect, build, and use data as we grow. Location & work mode Linear is a remote-first company, with optional co-working offices in San Francisco, New York, and London. This role is open to candidates based in North America. You can work from anywhere within this region. We value deep focus and async collaboration, with intentional moments to connect in person through team off-sites, optional co-working, and occasional travel. What you’ll do Work across Product and GTM (Marketing, Sales, Customer Success, and Finance) to turn ambiguous questions and operational needs into useful metrics, models, analyses, and workflows Build and maintain dbt models and pipelines that create trusted views of our product, customers, and business Design clear, maintainable data models and improve the testing, documentation, performance, and reliability of our data stack Build dashboards and self-service reporting in Metabase and Hex, and dig deeper when the answer requires more than a chart Operationalize data through reverse ETL and partner with GTM Engineering on the scoring, segmentation, a