{"id":2143937,"url":"https://alion.io/job/strava-senior-data-engineer","title":"Senior Data Engineer","company":{"id":3883,"name":"Strava","domain":"strava.com","url":"https://alion.io/company/strava","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":175000,"max":190000,"currency":"USD","period":"year","gross":null,"usd_annual":190000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Amazon Redshift","optional":false},{"name":"Apache Kafka","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"BigQuery","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"dbt","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Flink","optional":false},{"name":"GCP","optional":false},{"name":"GDPR","optional":false},{"name":"Go","optional":false},{"name":"Google BigQuery","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Snowflake","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Jackson","optional":true}],"status":"live","first_seen_at":"2026-10-01T02:21:57Z","employer_posted_date":"2026-10-01","last_verified_at":"2026-10-13T01:42:34Z","board_verified":true,"closed_at":null,"days_open":12,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":12},"description":"About Strava\nStrava is the app for active people. With over 200 million athletes in more than 185 countries, it’s more than tracking workouts-it’s where people make progress together, from new habits to new personal bests. No matter your sport or how you track it, Strava’s got you covered. Find your crew, crush your goals, and make every effort count. Start your journey with Strava today.\nOur mission is simple: to motivate people to live their best active lives. We believe in the power of movement to connect and drive people forward.\nAbout This Role\nWe are looking for a Senior Data Engineer to join our Data Team and help build reliable, scalable data systems that support analytics, data science, and critical business use cases across Strava.\nIn this role, you will design and operate data pipelines, build high-quality domain data models, improve our dbt and data transformation workflows, and help ensure data is accurate, well-governed, and easy to use. You will also contribute to areas such as data ingestion, data quality, privacy and GDPR workflows, and the ongoing evolution of our data warehouse and data lake.\nWe follow a flexible hybrid model that translates to more than half of your time on-site in our San Francisco office - three days per week.\nWhat You’ll Do:\nDesign, build, and operate foundational data systems and shared data assets that serve a broad range of analytical, operational, and business use cases across Strava.\n\nBuild and evolve scalable data ingestion and transformation frameworks that move, process, clean, standardize, and organize data across our data lake and data warehouse.\n\nDevelop reusable data engineering tools and abstractions that improve how engineers build and operate data pipelines, including frameworks and capabilities around technologies such as dbt.\n\nDesign high-quality, durable domain data models - such as user, subscription, activity, or other core business domains - that provide consistent definitions and reusable foundations for teams across the company.\n\nBuild systems and workflows that support data governance, privacy, and regulatory requirements, including GDPR-related deletion, retention, access, and data lifecycle management.\n\nImprove the reliability and observability of our data platform through automated testing, data quality checks, lineage, monitoring, alerting, and operational tooling.\n\nOptimize large-scale data processing and storage for performance, maintainability, scalability, and cost across both warehouse and data lake environments.\n\nPartner with data engineers, analytics engineers, software engineers, data scientists, security, privacy, and infrastructure teams to establish scalable data architecture and engineering standards.\n\nYou will be successful here by:\nThinking beyond individual pipelines and designing reusable systems, abstractions, and data models that solve common problems across multiple teams and use cases.\n\nBuilding well-defined domain data assets with clear semantics, ownership, lineage, and interfaces so downstream consumers can confidently build on top of them.\n\nApplying strong data modeling principles to represent complex business entities and relationships in ways that are extensible, understandable, and efficient.\n\nMaintaining a high bar for data correctness, reliability, privacy, and operational excellence across critical production data systems.\n\nMaking thoughtful engineering tradeoffs across data freshness, scalability, storage, compute cost, complexity, and developer productivity.\n\nProactively identifying recurring pain points in the data development lifecycle and creating tooling or platform capabilities that eliminate manual work and improve engineering velocity.\n\nDesigning data systems with governance and regulatory requirements in mind, rather than treating privacy and compliance as downstream concerns.\n\nBringing software engineering discipline to data infrastructure through testing, modular design, version control, CI/CD, observability, documentation, and code review.\n\nWhat You’ll Bring to the Team:\nYou have 3-5+ years of professional experience in Data Engineering, Data Infrastructure, Software Engineering, or a related field, with experience owning production data systems.\n\nYou have strong expertise in SQL and data modeling, including experience designing dimensional, normalized, or domain-oriented data models for large-scale analytical systems.\n\nYou have experience building and operating ETL/ELT and data processing systems using technologies such as dbt, Airflow, Spark, or similar frameworks.\n\nYou have experience developing reusable tooling, frameworks, or abstractions that improve how data pipelines and transformations are built, tested, deployed, or operated.\n\nYou are proficient in at least one general-purpose programming language such as Python, Scala, Java, or Go and are comfortable applying software engineering principles to data systems.\n\nYou understand modern data warehouse and data lake architectures and have worked with technologies such as Snowflake, Databricks, BigQuery, Redshift, Iceberg, Delta Lake, or similar systems.\n\nYou have experience processing and transforming large datasets, including handling schema evolution, data normalization, deduplication, backfills, incremental processing, and data quality.\n\nYou understand data governance and data lifecycle concepts such as lineage, retention, deletion, access control, PII handling, and GDPR/privacy requirements.\n\nYou have experience implementing production-grade data quality, monitoring, alerting, testing, and observability for data pipelines and datasets.\n\nYou can independently reason about data architecture and make sound technical decisions around modeling, ingestion, transformation, storage, reliability, scalability, and maintainability.\n\nYou are comfortable working with cloud infrastructure such as AWS, GCP, or Azure and understand the infrastructure that supports large-scale data processing systems.\n\nExperience with Kafka, Flink or other streaming systems; Kubernetes; Iceberg or other open table formats; data catalogs and lineage systems; schema management; CDC; or internal developer platforms for data engineering is a plus.\nFor information on benefits, please click here.\nWhy Join Us?\nMovement brings us together. At Strava, we’re building the world’s largest community of active people, helping them stay motivated and achieve their goals.\nOur global team is passionate about making movement fun, meaningful, and accessible to everyone. Whether you’re shaping the technology, growing our community, or driving innovation, your work at Strava makes an impact.\nWhen you join Strava, you’re not just joining a company-you’re joining a movement. If you’re ready to bring your energy, ideas, and drive, let’s build something incredible together.\nStrava builds software that makes the best part of our athletes’ days even better. Just as we’re deeply committed to unlocking their potential, we’re dedicated to providing a world-class, inclusive workplace where our employees can grow and thrive, too. We’re backed by Sequoia Capital, TCV, Madrone Partners and Jackson Square Ventures, and we’re expanding in order to exceed the needs of our growing community of global athletes. Our culture reflects our community. We are continuously striving to hire and engage teammates from all backgrounds, experiences and perspectives because we know we are a stronger team together.\nStrava is an equal opportunity employer. In keeping with the values of Strava, we make all employment decisions including hiring, evaluation, termination, promotional and training opportunities, without regard to race, religion, color, sex, age, national origin, ancestry, sexual orientation, physical handicap, mental disability, medical condition, disability, gender or identity or expression, pregnancy or pregnancy-related condition, marital status, height and/or weight.\nWe will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.\nCalifornia Consumer Protection Act Applicant Notice","description_format":"text","description_chars":8252,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Fitness","Social Networks"],"lifecycle":[{"event":"open","at":"2026-10-09T03:59:39Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 18 · green card filings: 1","filings_12m":18,"filings_prev_12m":11,"green_card_filings_12m":1,"median_offered_wage_usd":209342,"route":null,"cap_exempt":false,"checked_at":"2026-10-03T21:08:04+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":2}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":11,"expected_fill_days":78,"reasons":["conf:0","velocity","win:early"],"computed_at":"2026-10-12T06:55:09Z"},"pay":{"stated_usd_annual":190000,"is_top_pay":true},"html_url":"https://alion.io/job/strava-senior-data-engineer","json_url":"https://alion.io/job/strava-senior-data-engineer.json","meta":{"generated_at":"2026-10-13T03:20:20Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":5158,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-14T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":3883},"rest":"https://alion.io/mcp/rest/get_company?id=3883"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fstrava-senior-data-engineer"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fstrava-senior-data-engineer"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fstrava-senior-data-engineer"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/strava-senior-data-engineer\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fstrava-senior-data-engineer"}]}