Senior Data Engineer

As a Senior Data Engineer at Keyrock, you'll be one of the early hires in the Central Data Team (CDT), building the Keyrock Data Platform from the ground up. This platform gives Keyrockers and the AI agents working alongside them the data and context they need to act fast and autonomously. You'll work across the entire company, taking data from trading desks, wealth and asset management, product, risk, finance, compliance, and research, and making sense of it in real time. The standards we settle on and the way the team works are still open, so you'll contribute to most of the bigger decisions and build work.

What you'll do

• 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 (SDKs, patterns, templates, AI agents) so other teams publish, consume, and build on data products without waiting on you.
• Own data contracts and schema evolution, keeping 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: stale-feed detection, schema validation, range checks, idempotent writes, lineage, ownership, and self-healing.
• Build the derived analytics the business runs on: cross-exchange spreads, VWAP at depth, order book microstructure for the desks; portfolio views, exposure, and performance for wealth and asset management.
• Make observability, cost, and performance first-class from day one.
• Treat infrastructure as code (Docker, Terraform, CI/CD) alongside the Central Infrastructure Team.
• Work in the open: write things down and partner closely with Architecture, Infrastructure, Platform, and the rest of the teams.

What you bring

• 8+ years of building production data systems that other people rely on.
• Strong proficiency in Python and SQL: not just being able to write a query, but being able to reason about what the engine is doing with it.
• Code that is easy for someone else to read, test, and delete later.
• Strong understanding of data modelling for both streaming and analytical workloads.
• You take efficiency, quality, idempotency, and observability seriously by default.
• You have designed and operated streaming systems on Kafka, Redpanda, MSK, or Kinesis, and have opinions about partitioning, consumer groups, offsets, and schema registries.
• You have used a time-series store in production (ClickHouse ideally; TimescaleDB, QuestDB, or similar) and can talk about table design as a function of query patterns.
• You have worked with a lakehouse architecture and reason about table layout, partitioning, and compaction as design choices that shape query performance and storage cost.
• You build for self-healing and idempotency. Reprocessing is safe, retries do not double-write, and the system recovers without a human in the loop.
• Docker, Terraform, and CI/CD are how you work, not a separate DevOps function.
• You think about cost and performance early.
• You instrument as you build: logs, metrics, and traces are part of the system from day one.
• You design for data quality and governance up front, covering contracts, validation, lineage, and ownership.
• You reason from first principles when a problem is new, stay pragmatic when it is not, and update your view when you learn more.
• You treat trading desks, wealth and asset management, product, risk, finance, compliance, and research as customers of what you build, and communicate with them that way.
• You optimise for outcomes over output. A smaller, simpler thing that ships and works beats a bigger thing that does not.
• You take ownership end-to-end: design, ship, operate, and improve.
• You say what you think, including when it is an unpopular take. You change your mind when the argument is better.
• You make the people around you better. Reviews are real, juniors grow from working with you, and peers want to work with you again.
• You are curious about how markets work. Data engineering on its own will not keep you interested here.
• You are honest about what you know and what you do not, and quick to close the gap.
• You understand financial market data: order books, trades, reference data, portfolios, and exposures. Crypto, TradFi, or both are a strong plus.

Nice to have

• Lakehouse experience with Apache Iceberg or Delta Lake.
• Familiarity with DataHub or similar metadata and lineage platforms.
• Rust. Some of our performance-critical services are written in it. Interest is welcome; fluency is not required.

What we offer

• A from-scratch mandate. You will be among the first hires in CDT, and the platform, the standards, and the team culture are yours to shape with us.
• Strong partners. Close working relationships with Architecture, Infrastructure, Platform, and the desks themselves.
• Autonomy on how you work. Flexible hours, remote-first, and business-hours on-call shared across the team.
• A competitive salary package with various benefits.
• A team that likes each other. Regular online get-togethers and a yearly onsite where everyone is in the same room.

About Keyrock

Since 2017, Keyrock has grown to be a leading change-maker in the digital asset space. Today, the team spans over 250 members across 42 nationalities, with hubs in London, Brussels, and Singapore. Keyrock trades on more than 80 venues and offers services spanning market making, options trading, high-frequency trading, OTC, and DeFi trading desks. The company is a pioneer in adopting Rust for algorithmic trading and supports Web3 growth through its Accelerator Program while injecting liquidity into DeFi, RWA, and NFT protocols.