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PolymarketPolymarketNew York, NY

Senior Data Engineer

Builds and scales OLAP/OLTP data platforms for prediction market analytics, handling event ingestion, data modeling, streaming pipelines, and low-latency serving at crypto scale. Requires 5+ years experience with columnar warehouses like ClickHouse, Kafka, PostgreSQL, and data lakes.

Salary not listed
On-site5+ YOEData Engineering

About the role

What You'll Do

  • 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. Own materialized view design, refresh cadences, dictionary catalog, query planning, and cost optimization.
  • 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.
  • 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.
  • 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.
  • Coordinate across teams. Negotiate schema contracts with the warehouse-owning team and downstream consumers including frontend, notifications, and third-party integrators.

What We're Looking For

  • 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
  • PostgreSQL at scale: partitioning, index design, autovacuum/bloat remediation, query planning, CDC triggers vs. logical replication
  • 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
  • Rust: you'll touch indexer and validation tooling codebases; comfortable reading and contributing
  • Domain knowledge in DeFi, prediction markets, or order-book systems
  • Observability and SLO thinking: Prometheus metrics design, dashboard discipline, alert-fatigue avoidance
  • Python for SQL tooling, ad-hoc analysis, and one-off migrations
  • Track record shipping a platform migration or greenfield data stack under a hard deadline

Benefits

  • Competitive salary & equity
  • Unlimited PTO
  • Full Health, Vision, & Dental coverage
  • 401k match
  • Hardware setup: new MacBook Pro, big display, & accessories

Skills

ClickHouseKafkaPostgresIcebergParquetSnowflakeBigQueryRedshiftApache PinotSQLPythonRust

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