Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . We are looking for a talented and driven individual to be a key part of our Analytics Engineering team within the Data Science organization. We are looking for someone who can work closely with Data Scientists and Engineers across diverse areas of the organization (Consumer, Ads, and Marketing) to curate, develop, and deploy the right data and analytic tooling to drive Reddit’s product forward and provide a data and tooling foundation that will last decades. Your work will empower thousands of your colleagues to improve the user experience and grow our consumer base. Successful candidates have a strong track record of understanding and deeply caring about the purpose of data to support business goals, and can act as an effective conduit between Data Producers and Data Consumers. This role sits at the intersection of Data Science and Data Engineering, and the ideal candidate has skills, experience, and passion in both areas. Responsibilities: Be a key contributor and collaborator to the success of data quality, performance, reliability, and automation initiatives. Manage a portfolio of data products that deliver high-quality, trustworthy data Develop and maintain robust data pipelines and workflows for data ingestion, processing, and transformation. Work closely with engineering to ensure the quality and reliability of these data pipelines. Develop and implement data quality checks, conduct QA and implement monitoring routines Create and manage new data integrations across internal and external systems Create tools and a
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At Freddie Mac, our mission of Making Home Possible is what motivates us, and it’s at the core of everything we do. Since our charter in 1970, we have made home possible for more than 90 million families across the country. Join an organization where your work contributes to a greater purpose. Position Overview: We need a highly innovative Technical Lead! How confident are you that you can build sophisticated analytic systems? If you believe you could contribute to the development of innovative principles and ideas in a matrixed environment, please keep reading as we are seeking an individual contributor who has experience with Java and Python and can lead and nurture an inspiring environment in our Virginia office. Our Impact: The Investments and Capital Markets (I&CM) division is looking for a capable technology lead for its trading and analytics development team. This could be you! To thrive in this division, you must have a comprehensive understanding of system implementation and design, experience working in capital markets, and be enthusiastic about leading development of new paradigms in software system architecture. Your Impact: As a Trading Analytics Development Tech Lead, you will develop and maintain software using Java and Python tech stack that adheres to software engineering best practices. You will influence technical decisions, mentor developers, resolve engineering blockers, and partner with engineering managers to help teams deliver secure, reliable, and maintainable solutions. You will provide hands-on directions for full-stack applications, APIs, microservices, and integration services while reinforcing engineering discipline across design, development, testing, deployment, observability, and production readiness. Partner closely with Product Owners, engineering managers, architecture, business stakeholders, and cross-functional tec
We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview About the Role We are currently seeking a Senior Software Engineer to join our Agentic Analytics Platform team — the team responsible for the AI-for-Data charter inside Instacart's Data Infrastructure org. You'll design and build LLM-powered systems that transform how data practitioners (data scientists, data engineers, analysts, PMs) interact with data at Instacart — from natural-language data access and AI-assisted SQL, to automated metadata generation, to embedding intelligent capabilities across our broader data infra ecosystem. This is a hands-on role at the frontier of applied AI inside a large, modern data stack. About the Team The mission of the Instacart Self-Serve organization is to improve the productivity of data practitioners through easy-to-use, self-serve tools. Agentic Analytics is the team chartered with bringing AI and LLMs into that miss
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. Financial Systems owns the data and reporting foundation for Accounting, and the operational reliability of the pipelines that power reporting, reconciliations, and automation. We are building a single source of truth for financial information using dbt and Snowflake to enable scalable BI and process automation across the org. We are hiring an Analytics Engineer focused on maintaining and optimizing our finance data platform , improving reliability, efficiency, and performance of our pipelines and core datasets. This role is ideal for someone who enjoys operational ownership, building strong foundations, and making data systems easier and safer to run at scale. What You’ll Do Build and maintain dbt models and core datasets that support Accounting reporting and downstream automation use cases. Improve platform reliability through strong testing patterns, alerting, and runbooks. Own and document data pipelines and lineage, ensuring changes are understandable and auditable. Identify, troubleshoot, and resolve production data issues, and drive root-cause fixes. Optimize performance and cost in Snowflake and dbt to support scaling needs. Partner with engineering and business stakeholders to translate requirements into durable, well-tested data assets. Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows). What We Look For 3+ years of experience in analytics engineering, data engineering, or similar roles working with production data systems. Strong SQL skills and hands-on experience building in dbt (modeling, testing, documentation). Experience operating in a modern development workflow: Git and pull-request based collaboration (GitHub preferred). Familiarity with standard IDEs and collaborative debugging practices. E
Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. Join the engineering team that builds the AI-native apps, agents, and tools the rest of Amplitude runs on. We are full stack, automation, integration, and data engineers delivering internal apps, data products, automations, and integrations to Finance, People Ops, Product Ops, Legal, HR, and more. We embed in each team, become experts in their business problems, partner on the solution, and accelerate time-to-value. This is an AI-first, full-stack software engineering role spanning the complete scope of our team’s work. Your engineering experience and fluency with frontier AI technologies will drive continuous improvements in both the systems we build the way we build them. The sum total of this work will produce meaningful business impact on the way all of Amplitude’s critical business functions operate. As a Senior Software Engineer, you will: Desi
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. Financial Systems owns the data and reporting foundation for Accounting, and the operational reliability of the pipelines that power reporting, reconciliations, and automation. We are building a single source of truth for financial information using dbt and Snowflake to enable scalable BI and process automation across the org. We are hiring an Analytics Engineer focused on maintaining and optimizing our finance data platform , improving reliability, efficiency, and performance of our pipelines and core datasets. This role is ideal for someone who enjoys operational ownership, building strong foundations, and making data systems easier and safer to run at scale. What You’ll Do Build and maintain dbt models and core datasets that support Accounting reporting and downstream automation use cases. Improve platform reliability through strong testing patterns, alerting, and runbooks. Own and document data pipelines and lineage, ensuring changes are understandable and auditable. Identify, troubleshoot, and resolve production data issues, and drive root-cause fixes. Optimize performance and cost in Snowflake and dbt to support scaling needs. Partner with engineering and business stakeholders to translate requirements into durable, well-tested data assets. Contribute to the team’s best practices in version control, code review, documentation, and release hygiene (GitHub-based workflows). What We Look For 3+ years of experience in analytics engineering, data engineering, or similar roles working with production data systems. Strong SQL skills and hands-on experience building in dbt (modeling, testing, documentation). Experience operating in a modern development workflow: Git and pull-request based collaboration (GitHub preferred). Familiarity with standard IDEs and collaborative debugging practices. E
About the Team The Platform Analytics team builds the systems OpenAI researchers use to understand the quality and behavior of the models we train including what models are doing, why they behave in a particular way, and how that behavior changes across experiments. Neptune is a core part of this work. It ingests, stores, queries, and visualizes large volumes of metrics from pretraining, post-training, and reinforcement learning. Hundreds of researchers depend on these systems in their daily work to compare experiments, debug unexpected behavior, and decide what to try next. Our scope is broader than metrics. We also build platforms that help researchers analyze samples, traces, evaluation results, and other structured or unstructured data through dashboards, APIs, and increasingly agent-driven workflows. These systems need to remain fast, reliable, and understandable as the scale and complexity of research change quickly. We are not trying to become a consulting team that builds a separate solution for every research project. We work directly with researchers to understand recurring problems, then turn them into reusable infrastructure and platform capabilities that many teams can build on. About the Role We’re looking for a hands-on experienced software engineer who can take ownership of a critical system and drive it from problem definition through production adoption. This person should be able to own a platform such as CacheHouse end to end: define its technical direction, design its data model and storage architecture, integrate it with several research dashboards and workflows, guide one or two engineers, and ensure the system works reliably for its users. The right candidate should already bring the technical judgment, ownership, and execution expected at this level. The primary learning curve should be OpenAI’s stack and research problem space, not learning how to lead a complex engineering effort or deliver a production system. You will work directly with
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role As a Marketing Analytics Lead at Anthropic, you will own how we measure marketing. You'll build and run a single measurement framework that shows how marketing activity turns into pipeline, revenue, and product usage, and you'll make that framework something marketers and executives actually use to make decisions. As our marketing programs grow across enterprise and product-led motions, your work will determine whether we invest in what works. In this role, you'll own the marketing measurement framework end to end: the metric definitions, the data models behind them, the dashboards that surface them, and the insights they produce. This is a hands-on individual contributor role; data science and data engineering will support you, but you'll do the core work yourself. You'll partner closely with field marketing, partner marketing, campaign marketing, finance, sales strategy, sales development, data science, and data engineering to align on definitions and keep the whole organization working from one view of the funnel. Key responsibilities Own the marketing measurement framework that connects marketing activity to pipeline, revenue, and product usage Set the direction for the framework and extend it to programs it doesn't cover yet Define marketing metrics clearly and get cross-functional teams to agree on definitions early Build and maintain the data models that power marketing reporting Develop dashboards that marketers and executives rely on in their weekly reviews Teach marketers and executives how the metrics work, and keep teaching as the metrics evolve Lead adoption of the framework so that both marketing and execu
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 Analytics organisation sits at the heart of Deliveroo powering decision-making across our 3 sided marketplace. We’re looking for an Analytics Engineering Manager to join our London team. This is a hybrid role, with 3 days per week on-site. In this role, you’ll lead a team of Analytics Engineers embedded in a key business domain, owning the pipelines, models and metrics that power day-to-day decisions and building the data foundations your stakeholders rely on. About the Analytics Engineering Org Analytics Engineering is a core pillar of Deliveroo’s Analytics organisation, alongside Data Science. With over 70 Analytics Engineers across the UK and India, we are embedded directly within product and business domains, owning the pipelines, models and metrics that power decision-making at scale: from self-serve AI-enabled analytics and experimentation through to executive reporting and strategic planning. The discipline is evolving fast. With new tooling changing how we work, we are shifting from building data pipelines to building AI first data products, developing rich semantic and data context layers and empowering self-serve data users. This role leads that work across a defined business domain, directly managing a team of Analytics Engineers and helping shape AE standards, culture and direction across the wider org. What You'll Be Doing Directly lead a team of Analytics Engineers embedded in a defined business domain, owning their performance, development and wellbeing Own the AE roadmap for your domain, identifying the highest-
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 Job Requirements Mandatory Foundations 5+ years production experience with both Python and Java in high-performance environments Strong software engineering fundamentals: system design, data struct
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role We are seeking a Recruiting Analytics Data Engineer to join our People Data Solutions team, focusing on building and maintaining the data infrastructure that powers our recruiting analytics capabilities. You'll be the technical foundation for our recruiting analytics team, designing scalable data architectures and implementing robust data models that enable evidence-based decision-making across Anthropic. This role sits at the intersection of data engineering and recruiting analytics - you'll build the technical foundation for insights about recruiting funnels, interviews, and workforce planning while working with a team that's actively experimenting with AI to transform how we understand and support our workforce. Key responsibilities Data Infrastructure & Modeling Refactor and optimize our existing BigQuery tables to create a scalable data foundation that supports and enables AI-driven data insights across the company Design scalable data architectures and build dimensional models that transform raw HR data into trusted, reusable datasets for self-serve analytics while maintaining performance Implement data governance including documentation, lineage tracking, quality monitoring, and proactive alerting systems Ensure appropriate data access controls including row and column-level security for sensitive candidate data Pipeline Development & Integration Build and maintain ETL/ELT pipelines using dbt and Google BigQuery to integrate data from our HRIS (Workday), ATS (Greenhouse), and internal tools Create reliable data flows that handle both real-time needs and batch processing requirements Design fault-tolerant
About Mixpanel Mixpanel is the leading product intelligence and analytics platform, trusted by more than 29,000 companies to help understand how people use the products they build. By combining powerful analytics with AI that knows your business, Mixpanel helps teams see what’s working, diagnose what’s not, and decide what to build next. Learn more at mixpanel.com . About Mixpanel Mixpanel turns data clarity into innovation. Trusted by more than 29,000 companies, including Workday, Pinterest, LG, and Rakuten Viber, Mixpanel’s AI-first digital analytics help teams accelerate adoption, improve retention, and ship with confidence. Powering this is an industry-leading platform that combines product and web analytics, session replay, experimentation, feature flags, and metric trees. Mixpanel delivers insights that customers trust. Visit mixpanel.com to learn more. About The Team Mixpanel Engineering is a small, fast-moving team focused on delivering real value to customers. We build powerful AI-powered product analytics while obsessing over clarity, simplicity, and delight. Engineers here own problems end to end. You can move across the stack to ship impact without being blocked by silos or heavy process. Product innovation drives our business, and product engineering teams own that responsibility. Our OLAP engine queries over 500 trillion events; a typical blob storage system we interact with processes 300 PiB/month at 1.2 Tbps sustained, and we run many of them across the world. The Data Runtime team owns the data execution layer that powers every Mixpanel product. We ensure that every customer query runs fast, cheap, and reliably, at any scale. This is an exciting time to join. Mixpanel's agentic and AI-first products are driving rapid growth in query volume, and Data Runtime is making the big bets that power it. We’re investing in elastic query compute and a distributed file cache that will let us scale query workloads dramatically without scaling cost with th
We are looking for a strategic Business Process Manager to architect the agentic transformation of our GTM tech stack. The GTM Ops, Strategy, Field Readiness, and Sales Development team at Asana enables growth, efficiency, and performance at scale through the strategic management of revenue operations, systems, strategy + analytics, and enablement. In this role, you will act as a thought partner to business stakeholders, a designer of future-state workflows, and the connective tissue between the business and Enterprise Technology (ET). You will own our end-user CPQ experience, drive our agentic quoting capability, and solve complex system dependencies across the broader GTM ecosystem to help Asana scale. This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Partner as a key cross-functional thought leader with Sales, RevStrat, ET, Deal Desk, and Finance to design scalable, AI-ready workflows that accommodate evolving GTM motions. Own the strategy, requirements gathering, and adoption health of our CPQ platform and agentic quoting capabilities. Scope, prioritize, and manage enhancements across the Salesforce Opportunity object and broader GTM stack to maximize data integrity and cross-functional alignment. Execute end-to-end UAT by authoring test scenarios, managing edge cases, and establishing a reusable UAT framework for future releases. Resolve handoff failures across system integration points to optimize downstream operations across Deal Desk, Provisioning, Order Management, and Billing. Deliver transparent communication and regular updates regarding project timelines, success metrics, an
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 Analyst at 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 founda
About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We are looking for a Finance & Strategy (FP&A) Systems Engineer to join our Finance Systems team at Anthropic. In this role, you will be responsible for building and maintaining platforms that support our core Financial Planning, Forecasting and Analytics processes. You will bring deep hands-on expertise in EPM platforms like Anaplan, Pigment and data platforms like BigQuery, who writes integrations, tooling, and production code that connect them to Anthropic’s ERP and data warehouse systems. You'll work closely with Corporate Finance & strategy stakeholders to translate business requirements into innovative technical solutions, maintain data integrity, and drive continuous improvements to our financial systems infrastructure. You'll manage day-to-day Finance system operations, support critical financial processes and monthly Forecasting cycles, and take on more ambitious system projects over time, including using Claude to automate FP&A work, help build scalable solutions that enable efficient financial planning, forecasting, and reporting as we continue to grow. Responsibilities Systems Administration and Support Serve as a primary system administrator for our financial planning platform (Pigment), maintaining system health and optimal performance Manage Finance applications, data, user access & security, system configurations, version management to ensure appropriate controls and governance. Provide technical support and troubleshooting for end-users, resolving issues and answering system-related questions System Development and Enhancement Design, build, and maintain application
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