Senior Data Engineer

About UsVolley is the leading developer of AI-powered games for Amazon Alexa, Samsung, LG, Roku, Fire TV, and mobile devices. Our games attract millions of users every month. Popular Volley games include Song Quiz, Jeopardy!, CoComelon: Sing and Play with JJ, and The Price Is Right.We believe voice interfaces will become the main way people access entertainment in their living rooms, kitchens, bedrooms, and cars. We’re building a bundled subscription product similar to Netflix or Spotify for the emerging category of “AI-powered games.”Volley was founded by Max Child and James Wilsterman in 2016 and went through Y-Combinator in 2018, landing a spot on the 2022 YC Top Companies List. We’re a quickly-growing team that truly enjoys working together, headquartered in downtown San Francisco in the historic Phelan Building.Role SummaryVolley is seeking our first Data Engineer to build the foundation for production-grade data infrastructure and unlock the next phase of our growth. You'll own end-to-end data pipelines for marketing attribution, design scalable orchestration patterns, and establish the reliability standards that turn growth data into a dependable system. This is a high-impact opportunity to create durable infrastructure from the ground up and materially improve marketing efficiency.What You'll Do at VolleyBuild and own end-to-end data pipelines, including attribution and third-party enriched data sources (ingestion → orchestration → warehouse → consumption).Establish production-grade reliability standards: monitoring, alerting, SLAs, observability, runbooks, and incident response.Design scalable patterns for handling late/out-of-order data, backfills, historical consistency, and data quality.Implement environment separation (dev/stage/prod), CI/CD for pipelines, and data contracts/validation frameworks.Collaborate with Data, Growth, and Engineering teams to define data requirements and enable confident decision-making.Lay the groundwork for unified attribution and incrementality frameworks that drive marketing spend optimization.Turn today's brittle, ad-hoc pipelines into production-grade systems that increase velocity and reduce fire drills.We're Excited About You Because You Have5+ years of data engineering experience with a proven track record of building reliable production pipelines.Deep expertise with orchestration tools (Airflow, Prefect, or Dagster) including scheduling, retries, alerting, and SLAs.Strong proficiency in Python and SQL, with experience building ELT/ETL pipelines at scaleHands-on experience with modern data warehouses (Snowflake, BigQuery, or Redshift).Deploying and operating pipelines in cloud (IAM, networking basics, secrets, CI/CD).Track record of improving data reliability: handling schema drift, late data, backfills, and operational incidents.Experience making data production-ready with proper monitoring, documentation, and ownership.Bonus PointsExperience with marketing attribution or growth analytics pipelines.Background in analytics engineering (dbt, SQLMesh, Dataform) or strong understanding of data consumer needs.Gaming or entertainment industry experience.Early-stage startup experience building with limited resources.Familiarity with observability tools.Our StackSnowflakeTableau, Amplitudedbt, Airflow, DagsterSegment, FivetranLanguages: Python, SQLThe Hiring ProcessStage 1 (Preliminary Video Call): with a member of our Recruitment teamStage 2 (Hiring Manager + Technical Call): A call with the team's Hiring Manager followed by a technical session with one of our Analytics Leads.Stage 3 (Onsite Interview): with various partners and team membersStage 4 (Founder Chat) with our FoundersAs an AI company, we’re a huge believer in the value of AI tools. That being said, the interview process is intended as a conversation - we want to get to know you and your experience. Please refrain from using AI tools during all Volley interviews unless otherwise specified.What’s in it for YouYour medical, ... (truncated, view full listing at source)