Senior Data Engineer

About the role

Keyrock is a market maker in digital assets, offering market making, options trading, high-frequency trading, OTC and DeFi trading desks, and is known for using Rust in algorithmic trading. Its Central Data Team (CDT) is building a data platform that feeds trading desks, wealth and asset management, product, risk, finance, compliance and research in real time. This is an early-hire position in CDT, with significant influence over the platform, standards and team culture.

Key responsibilities

• Build streaming and batch pipelines that ingest, normalise and distribute market, trading and portfolio data, resilient to feed and exchange failures.
• Build self-serve tooling (SDKs, patterns, templates, AI agents) so other teams can publish, consume and build on data products.
• Own data contracts and schema evolution, keeping schema changes from becoming multi-team coordination events.
• Design the lakehouse and time-series layer around consumer query patterns.
• Build and evolve the data governance and data quality framework: stale-feed detection, schema validation, range checks, idempotent writes, lineage, ownership and self-healing.
• Build derived analytics such as cross-exchange spreads, VWAP at depth, order book microstructure, portfolio views, exposure and performance.
• Make observability, cost and performance first-class from day one, and work with the infrastructure team using Docker, Terraform and CI/CD.

Required profile

• 8+ years building production data systems that others rely on.
• Strong understanding of data modelling for streaming and analytical workloads, with efficiency, quality, idempotency and observability built in.
• Experience designing streaming systems (partitioning, consumer groups, offsets, schema registries) and time-series stores, with a focus on self-healing and idempotency.
• Lakehouse experience and reasoning about table layout, partitioning and compaction.
• Operational readiness: Docker, Terraform and CI/CD, early cost and performance thinking, logging, metrics and tracing, data quality and governance up front.
• First-principles thinking, customer-focused communication with trading desks, wealth and asset management, product, risk, finance, compliance and research, and ownership end to end.
• Interest in how markets work; knowledge of financial market data (order books, trades, reference data, portfolios, exposures) is a strong plus.

Required skills

• Python and SQL
• Kafka, Redpanda, MSK or Kinesis
• Time-series store (ClickHouse preferred; TimescaleDB, QuestDB or similar acceptable)
• Docker, Terraform and CI/CD
• Nice to have: Apache Iceberg or Delta Lake, DataHub or similar metadata platforms, Rust

What we offer

• A from-scratch mandate with flexible hours and remote-first work, with business-hours on-call shared across the team.
• Close working relationships with Architecture, Infrastructure, Platform and the trading desks.
• A competitive salary package with various benefits.
• Regular online get-togethers and a yearly onsite event.