Data Engineer

Keyrock is a leading change-maker and market maker in the digital asset space, providing services that span market making, options trading, high-frequency trading, OTC, and DeFi trading desks while also supporting Web3 startups and upgrading ecosystems through liquidity injection and research initiatives.

• Build streaming and batch pipelines that ingest, normalise, and distribute market, trading, and portfolio data, resilient to feed and exchange failures;
• Build the self-serve tooling, including SDKs, patterns, templates, and AI agents, so other teams publish, consume, and build on data products without waiting on the central team;
• Own data contracts and schema evolution, and keep schema changes from turning into 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 covering stale-feed detection, schema validation, range checks, idempotent writes, lineage, ownership, and self-healing;
• Build the derived analytics the business runs on, such as cross-exchange spreads, VWAP at depth, order book microstructure for the desks, and portfolio views, exposure, and performance for wealth and asset management;
• Make observability, cost, and performance first-class from day one;
• Treat infrastructure as code using Docker, Terraform, and CI/CD alongside the Central Infrastructure Team;
• Work in the open by writing things down and partnering closely with Architecture, Infrastructure, Platform, and other teams.

• Bring 8+ years of experience building production data systems that other people rely on;
• Demonstrate strong proficiency in Python and SQL with the ability to reason about what the engine is doing with a query;
• Write code that is easy for someone else to read, test, and delete later;
• Have a strong understanding of data modelling for both streaming and analytical workloads;
• Take efficiency, quality, idempotency, and observability seriously by default;
• Design and operate streaming systems on Kafka, Redpanda, MSK, or Kinesis with knowledge of partitioning, consumer groups, offsets, and schema registries;
• Use a time-series store in production, ideally ClickHouse, TimescaleDB, QuestDB, or similar, and talk about table design as a function of query patterns;
• Work with a lakehouse architecture and reason about table layout, partitioning, and compaction as design choices that shape query performance and storage cost;
• Build for self-healing and idempotency so reprocessing is safe, retries do not double-write, and the system recovers without a human in the loop;
• Use Docker, Terraform, and CI/CD as standard working methods rather than separate DevOps tasks;
• Think about cost and performance early;
• Instrument as you build so logs, metrics, and traces are part of the system from day one;
• Design for data quality and governance up front covering contracts, validation, lineage, and ownership;
• Reason from first principles when a problem is new, stay pragmatic when it is not, and update your view when you learn more;
• Treat trading desks, wealth and asset management, product, risk, finance, compliance, and research as customers and communicate with them that way;
• Optimise for outcomes over output by choosing smaller, simpler things that ship and work over bigger things that do not;
• Take ownership end-to-end across design, shipping, operation, and improvement;
• Say what you think, including unpopular takes, and change your mind when the argument is better;
• Make the people around you better through real reviews, mentoring juniors, and being a valued peer;
• Understand how markets work and show curiosity about financial market data including order books, trades, reference data, portfolios, and exposures;
• Nice to have: Lakehouse experience with Apache Iceberg or Delta Lake, familiarity with DataHub or similar metadata and lineage platforms, Rust, financial market data experience in Crypto, TradFi, or both.

• Enjoy a from-scratch mandate where you can shape the platform, standards, and team culture;
• Work with strong partners in Architecture, Infrastructure, Platform, and the desks;
• Benefit from autonomy in how you work with flexible hours, remote-first setup, and business-hours on-call shared across the team;
• Receive a competitive salary package with various benefits;
• Participate in regular online get-togethers and a yearly onsite where everyone is in the same room.