Polymarket - Senior Data Engineer
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Requirements
• 5+ years of data engineering on production systems serving real users at scale • Deep knowledge of OLTP/OLAP split architectures: you know when a row store wins, when a column store wins, and when to use both • Columnar warehouse expertise: ClickHouse strongly preferred; Snowflake, BigQuery, Redshift, or Apache Pinot accepted if fundamentals are solid • Data lake experience: Parquet, Iceberg (or Delta/Hudi), compaction strategies, S3 layout discipline • Streaming pipeline experience: Kafka, exactly-once vs. at-least-once reasoning, backpressure, consumer-group patterns, schema evolution • Strong data modeling fundamentals: star/snowflake, SCD patterns, CDC, idempotent event sourcing, dimensional vs. event-log tradeoffs • SQL fluency at warehouse scale: window functions, CTEs, dictionary-based enrichment, dialect specifics • Distributed systems reasoning: consistency models, event ordering, replay semantics, write-once vs. mutable state, reorg handling • (Plus) EVM indexing experience: rindexer, subgraphs, or comparable – this shortens ramp considerably • (Plus) • (Plus) Rust: you'll touch indexer and validation tooling codebases; comfortable reading and contributing • (Plus) • (Plus) Domain knowledge in DeFi, prediction markets, or order-book systems • (Plus) • (Plus) Observability and SLO thinking: Prometheus metrics design, dashboard discipline, alert-fatigue avoidance • (Plus) • (Plus) Python for SQL tooling, ad-hoc analysis, and one-off migrations • (Plus) • (Plus) Track record shipping a platform migration or greenfield data stack under a hard deadline • (Plus)
Responsibilities
• Own the OLAP analytics layer. Drive our columnar warehouse environment end-to-end: raw event ingestion → cleaned facts and dimensions → business aggregates → API-serving views. You'll own materialized view design, refresh cadences, dictionary catalog, query planning, and cost optimization. • Own the OLAP analytics layer. • Partner on the OLTP serving layer. Work closely with the team on high-write serving tables that back our product APIs – partition strategy, indexing, trigger pipelines, autovacuum tuning, and bloat monitoring – with sub-100ms read-path discipline. • Partner on the OLTP serving layer. • Shape streaming and data lake infrastructure. Define Kafka topic schema contracts, evolve the S3 lake layout with modern table formats, and contribute to parity-validation tooling that guards data correctness under migration pressure. • Shape streaming and data lake infrastructure. • Design data models at scale. Work with event-sourced, append-mostly data with chain-reorg semantics. Design the derivative analytics – PnL, realized/unrealized position tracking, cohort metrics – and formalize ownership boundaries between upstream ingestion and downstream analytics. • Design data models at scale. • Coordinate across teams. Negotiate schema contracts with the warehouse-owning team and downstream consumers including frontend, notifications, and third-party integrators. • Coordinate across teams.
Benefits
• Full Health, Vision, & Dental coverage • Hardware setup: new MacBook Pro, big display, & accessories
No credit card. Takes 10 seconds.