Data Centre Computer System Operators in San Francisco

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. At Airtable, we're passionate about democratizing software creation — empowering anyone to build powerful, flexible tools without writing code. With our shift to an AI-native platform, customers can now generate full apps and deploy AI agents directly into their workflows. Data engineering plays a critical role in this evolution by delivering the insights our teams rely on to improve user experience, measure agent impact, and understand how the business is performing at scale. As a Software Engineer, Data at Airtable, you'll make an enormous contribution to our data engineering efforts. You'll design and own mission-critical data pipelines to enable decision-making, partner with company leaders to create scalable data solutions, and launch innovative alerting and visualization solutions. The Team Our team is embedded in how Airtable understands itself as a business, working closely with Data Science and Analytics. What's unusual here: the platform you're instrumenting is the same one your customers use every day. When Airtable ships a new AI agent capability, you're among the first to wire it up, measure its adoption, and influence what gets built next. Product & AI Data Infrastructure This team builds and owns the foundational data pipelines that power product analytics across Airtable. As Airtable shifts to an AI-native platform, our work increasingly involves instrumenting and measuring AI product usage, building event pipelines for AI agents, surfacing AI-native adoption metrics in core business tables, and developing AI-powered data discovery tooling, including vector search over our catalog metadata. We partner closely with product analytics, product engineering, and data infrastructure to turn business question

Join the team shaping the future of AI at Scale. Scale builds RL environments: sandboxed replicas of the digital spheres where real knowledge work occurs and built from the operating data of the companies that actually hold it. As the Data Acquisition Lead , you will own the commercial motion that gets us that data end to end. You will figure out which companies sit on the data for the next domain worth owning and then go and get it. This is a zero-to-one function with no playbook. You should be prepared to wear many hats, from thesis-driven dealmaker to hands-on operator to technical translator between commercial and Research teams. You will: Map the supply side. Work backwards from where labs are pushing to the specific organizations holding the underlying data. Build a thesis on which domains are worth owning and in what order. Invent the deal structures. You'll work with Scale’s legal team to define the first version of how these transactions get priced. Close. Own it from cold outreach to signature. Close the loop with the technical side. You need to hold a real conversation about what makes a dataset trainable and become an expert in what makes this underlying data valuable. Build the machine. Do the work by hand first, then turn what you learn into a repeatable pipeline. Ideally, you’d have: 5+ years across some mix of business development, corp dev, commercial strategy, or early-stage GTM. The label matters less than a track record of building a commercial motion that didn't exist before you got there A strong track record of managing important external relationships Strong business judgment and the ability to evaluate partnership value quickly Clear communication skills and comfort working with senior stakeholders Ability to operate independently while staying closely connected to cross-functional teams A practical, hands-on approach to building new functions from the ground up Comfort working in fast-moving, ambiguous environments Experience in

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

About the Team The Analytics team is looking for experienced Data Scientists and Senior Data Scientists to guide measurement, strategy, and tactical decision-making across the company across a variety of teams and levels. Data Scientists at DoorDash work to uncover insights and turn them into relevant recommendations, driving decisions for the entire organization. Analytics is integral to all operational areas at DoorDash. Please apply here for all non-managerial levels within the following analytics teams: Consumer & Growth Business Operations Dasher & Logistics Customer Experience & Integrity Merchant, Ads & Sales New Verticals International Data Science About the Role As a Data Scientist at DoorDash, you'll use your quantitative background to mentor other scientists and dive into large datasets to guide decision-making. We solve a multitude of exciting challenges including customer acquisition, fraud and support, marketing, balancing supply and demand, new city launches, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… Use quantitative analysis and the presentation of data to see beyond the numbers and understand what drives our business Build full-cycle analytics experiments, reports, and dashboards using SQL, R, Python, or other scripting and statistical tools Work with and mentor junior analysts on how to use more advanced methods and solve challenges Produce recommendations and use statistical techniques and hypothesis testing to validate your findings Provide insights to help business and product leaders understand marketplace dynamics, user behaviors, and long-term trends Identify and measure levers to help move essential metrics and make recommendations Work backwards from understanding and sizing problems to ideating solutions Report aga

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The Role We are seeking a Pricing Implementation Analyst to join our Pricing team in the Lending Organization. This is an exciting role for someone to make a direct impact on the revenue of SoFi. As Pricing Implementation Analyst, you will be working closely with a world-class team of business leaders and data scientists to help SoFi implement, monitor, and advance pricing controls and the execution of pricing strategies across our consumer lending products. What you’ll do: Pricing Execution (60%) Materialize strategy implementation by translating high-level strategies into tactical steps, assessing system implication, and ensuring specifications are complete and aligned. Maintain robust audit trails and enforce governance requirements, including Jira and Gitlab process controls. Collaborate closely with Engineering teams to troubleshoot and resolve system issues, ensure successful pricing deployments, and continuously monitor data pipelines to verify pricing strategy is running as expected. Develop and maintain systematic validation functions to ensure implementation accuracy across all products Controls & Process Improvement (25%) Develop and maintain controls, including building automated validations alerts and anomaly/exception detection Tableau dashboards Identify opportunities to enhance execution

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The role The Data Science team is seeking a Senior Manager who will help support growth in our SIPS businesses by improving SoFi’s ability to execute with data. This is an exciting role for someone to leverage their Analytical, Engineering, and Management skills to lead a team of Data Scientists with high visibility and impact. You will serve as a data leader, balancing urgent requests and delivering high quality projects to key stakeholders, through a clear and repeatable data informed approach. You will create a culture of strong technical ownership, deliver impact with prioritization, support the growth of individual contributors, and hold the team accountable with high standards. You are expected to work cross-functionally, including: engineering, product managers, lifecycle marketing, data science, design, operations, finance, risk, legal, compliance, and executive teams to set business objectives, define product strategy, prioritize features, and execute on them. What you’ll do: Manage a team of Data Scientists supporting SoFi’s Checking and Savings, Invest, Credit Card, Protect, and Lantern businesses Collaborate with senior leaders and other stakeholders to identify and prioritize Data Science initiatives Set high standards for quality and on-time delivery. Recruit, grow, and reta

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a Data Scientist you will shape the future of people-facing and business-facing products we build at Pinterest. Your expertise in quantitative modeling, experimentation and algorithms will be utilized to solve some of the most complex engineering challenges at the company. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering,

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges—from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. We are looking for an experienced and highly motivated Data Scientist to join the Central Market Management team and lead key initiatives that enhance the quality of our overall decision-making. You’ll work cross functionally with other Data Scientists, Data Analysts, Product Managers, and Finance partners to make sure we are making the most financially efficient decisions to scale our business. You will identify gaps in our operational processes and measurements, and work to create strategies, frameworks, and models to help address them and deliver impact. Responsibilities Leverage data and analytical frameworks to identify opportunities for improving operational efficiency Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope Define and implement a robust attribution framework to evaluate the performance of high-stakes decisions Act as a technical lead, guiding other Data Scientists and fostering a culture of analytical excellence Write efficient, clean, production-level code (Python, SQL), ensuring reproducibility, documentation, and long-term maintainability of analytical assets B

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data is at the heart of Lyft Business's products and decision-making. We're looking to hire a Data Analyst to build the tools and analytics that drive revenue for the sales organization behind Lyft's B2B portfolio — a multi-billion-dollar book of business spanning healthcare, business travel, corporate commute, automotive, and transit. This team has real say in what gets built. You will be the analytical partner to our Sales and account teams — someone who can translate findings into a clear narrative for both technical and non-technical audiences. Responsibilities: Build the tools and analytics sales leaders use to grow their accounts — pacing views, account-health signals, territory and segment views that change what a rep or manager does next Field requests from Sales, Product, Finance, Legal, leadership, and external stakeholders, and decide what's worth building, what's worth a sharp piece of analysis, and what's out of scope Build and maintain production data pipelines, and automate recurring workflows, with documentation and validation clear enough that a teammate — or an AI agent — can use them without asking you first Define what the team's core metrics mean and where they live, so every dashboard, report, and tool returns the same answer to the same question Contribute to the internal tools and semantic layer — prompts, context, and guardrails — that let stakeholders query B2B data in natural language and trust what comes back Translate insights into a cohesive narrative and present technical findings to senior leadership and non-technical audiences Experience: Degree (or related work experience) with a focus in analytics, statistics, economics, computer science, or other quantitative fields 3+ years of experience in a data analytics or business intelligence role, ideally supporting a sales

About Us Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X , and discover the projects we’re solving on our Blog . Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role Join the Monetization team at Twitch, where we build the products that help creators make a living on the platform. You'll work on products like Subscriptions, Bits, and Gifting, and the pricing and packaging decisions behind them. You'll partner closely with product, engineering, finance, and data teams to measure the impact of new features, design and analyze experiments, and apply causal inference methods to inform decisions where A/B testing isn't possible. The work ranges from high-velocity experimentation on consumer-facing products to deeper pricing, policy, and segmentation analyses where causal identification is the central challenge. This role is well-suited for someone with a strong economics or causal ML foundation who wants to apply rigorous statistical thinking to real product decisions at scale. You'll need to be comfortable writing SQL, working with imperfect data, and partnering with stakeholders to turn analysis into product impact. Our team is based at Twitch HQ in San Francisco, CA. You can work in San Francisco, CA; New York, NY; or Seattle, WA You Will: Apply causal inference methods where experimentation isn't feasible Develop models and analyses that inform pricing, segmentation, and revenue optimization Design, run, and analyze A/B experiments Pa

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

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. The Core Data Platform organization owns all the infrastructure necessary to run an operationally efficient analytical data stack. About the Roles The Data Platform team spans data mobility frameworks, ingestion, infrastructure, tools, and governance. Together, they design and operate scalable compute and ingestion frameworks using technologies such as Spark, Flink, Kafka, Airflow, and modern lakehouse solutions, while also building abstractions and tools that simplify data workflows for engineers, analysts, and ML practitioners. In parallel, these teams establish strong data quality, cataloging, privacy, and compliance standards to ensure trust in analytics and regulatory adherence. As relatively high-impact teams, they offer engineers the opportunity to shape the roadmap, influence core platform decisions, and directly enable DoorDash’s business-critical insights and real-time personalization capabilities. You must be located in San Francisco, CA, Sunnyvale, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Drive vision & strategy for building the frameworks charter and position it to handle the challenges of a rapidly growing business. Scale the analytical platform for the increasing amounts of data and use cases. You will bring your expertise in building and operating high scale systems with a focus on reliability, scalability and cost efficiency. Collaborate with stakeholders building solutions on top of the platform Foster a positive and supportive work culture, upleveling others. We're excited about you because you have… B.S., M.S., or PhD. in Computer Science or equivalent. 2+ years of industry experience at our I4 level, 5+ years of industry experience at our I5 level Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in th

About the Team The Analytics team is looking for Data Scientists to guide measurement, strategy, and tactical decision-making using Advanced Analytics approaches, as we expand our platform across the globe. Data Scientists at DoorDash work to uncover insights and turn them into actionable recommendations, helping drive decisions for the entire organisation. Analytics is very integral to all operational areas at DoorDash. About the Role Data Science at DoorDash involves diving deeper into our data to solve crucial business problems, ideate & run experiments to solve for insights gleaned from this deep dive and work with a cross-functional team to drive real-world operational change. This is a rare operational and actionable data-driven experience. We solve many exciting challenges from all three sides of our marketplace including customer acquisition, balancing supply and demand, fraud and support, marketing, marketplace efficiency, and more. If you enjoy finding patterns amidst chaos, are excited to build a market from 0 to 1, and have experience using analytics to affect revenue, growth, operations or beyond, we're looking for someone like you! You're excited about this opportunity because you will… As a senior Individual Contributor, mentor and influence junior Data Scientists in investigating complex issues and uncovering key drivers of our business Influence the Product and Operations roadmap by making actionable recommendations based on data Interface frequently with senior leadership to showcase your team’s work and tackle complex business problems Drive measurement strategy for the area under scope, defining success metrics and implementing best practices around experiment design and statistical analysis Develop a strategic learning roadmap based on data observations, strategic questions, and hypotheses We're excited about you because you have… A degree in Math, Physics, Statistics, Economics, Computer Science, or a similar domain 8+ years of experi

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 fi nancial reporting. Team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Sta ff Software Engineer,Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs. You’re excited about this opportunity because you will... Own critical data systems that support multiple products/teams Develop, implement and enforce best practices for data infrastructure and automation Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services 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... 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects 6+ years experience working in data platform and data engineering 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 Pro fi ciency in programming languages such as Python/Kotlin/Scala 4+ years of experience in ETL orchestration and work fl ow management tools like Air fl ow Expert in database fundamentals, SQL, data reliability practices and distributed computing 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kaa/Flink/Spark Streaming Excellent communication skills and experience working