Data Engineer

Ostium is on a simple mission: make it possible for anyone with a digital wallet to trade stocks, commodities, currencies, and crypto with full transparency. No brokers, no freezes, no hidden spreads. We're replacing the opaque, offshore brokerage model with a transparent, permissionless trading stack built onchain. Every trade, deposit, and withdrawal is verifiable through open, auditable code. We've raised $27.9M+ from General Catalyst, Jump, LocalGlobe, Susquehanna (SIG), GSR, Alliance DAO, Soma Capital, Balaji Srinivasan, Meltem Demirors, and others.

We are seeking a Data Engineer (Monitoring & Parameter Systems) to build and operate the
analytics, observability, and parameter-proposal tooling that keeps Ostium safe and
economically correct. You will be the bridge between protocol mechanics (fees, spreads,
rollover, liquidations) and production-grade data systems. Your mandate is to translate models
and parameter frameworks into reliable pipelines, monitored services, and dashboards that
ensure the protocol consistently charges the right values across markets.

• Data Pipelines: Architect and maintain robust ingestion and transformation pipelines for
  on-chain events and market data using AWS-native services and scalable storage/query
  layers.

• Parameter Proposal Systems: Implement parameter models (dynamic spreads/impact,
  OI caps, risk limits, funding/rollover controls) as reproducible code, producing versioned
  proposal artifacts for review.

• Monitoring & Observability: Design Grafana dashboards and alerting for protocol
  health and economic correctness (execution costs, fee accrual, oracle quality,
  liquidations, OI usage), with clear runbooks.

• Backtesting & Validation: Build testing and replay frameworks to validate parameter
  changes on historical data, detect regressions, and quantify impact under stress
  scenarios.

• Productionization: Package models and pipelines into reliable jobs/services with
  CI/CD, automated tests, data quality checks, and continuous monitoring of outputs.

• Data Engineering Fluency: Strong experience in Python and relevant libraries for
  production pipelines (pandas/numpy), plus strong SQL and experience designing
  analytics tables/views for time-series and trading data.

• AWS Experience: Hands-on with core AWS tooling (e.g., S3, Athena/Glue, Redshift,
  ECS/EKS/Lambda, CloudWatch).

• Observability Experience: Proven ability to build monitoring systems with Grafana (and
  ideally Prometheus/Loki/Tempo), including alerting, metrics definition, and incident
  response workflows.

• Production Mindset: Experience turning research logic into robust libraries/services
  with testing, versioning, CI/CD, and reproducible environments

• Data scientist mindset and experience building/validating models or statistical checks
  (e.g., parameter tuning, anomaly detection, backtesting-style evaluation) and translating
  them into production metrics.

• Familiarity with DeFi or trading data (PnL, funding/rollover, leverage, liquidation
  mechanics) and the quirks of on-chain event streams.

• Experience with blockchain indexing tools (Subgraphs/The Graph, Dune, RPC log
  parsing) and handling schema drift across protocol upgrades.

• Experience with orchestration and data quality tooling (Airflow/Prefect/Dagster, dbt,
  Great Expectations/Soda) and building reliable data contracts.

• Competitive compensation package

• Opportunity to work with cutting-edge blockchain technology

• Collaborative environment with highly skilled team members

• Flexible work arrangements

• Professional development opportunities

This role is perfect for someone who is excited about building reliable data infrastructure and
monitoring systems, enjoys shipping production-grade analytics, and wants to operationalize the models and parameters that power on-chain RWA trading.

Interested candidates should submit their resume, GitHub profile, and links to relevant projects demonstrating production data pipelines, monitoring/alerting systems, or deployed modeling
workflows.