Senior Data Engineer

As a Senior Data Engineer at Keyrock, you'll build the Keyrock Data Platform from the ground up, giving traders, AI agents, and business functions across the company the real-time data and context they need to act fast and autonomously. You join the Central Data Team, a new group tasked with taking data from across the organisation and making sense of it for trading desks, wealth and asset management, product, risk, finance, compliance, and research. As one of the early hires, you'll shape the platform's standards, architecture, and culture.

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 covering 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, and 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 writing queries but reasoning about what the engine is doing.
• Code that is easy for someone else to read, test, and delete later.
• A 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, with opinions on partitioning, consumer groups, offsets, and schema registries.
• You have used a time-series store in production (ClickHouse ideally, or TimescaleDB, QuestDB, or similar) and can reason 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, ensuring reprocessing is safe, retries do not double-write, and the system recovers without human intervention.
• Docker, Terraform, and CI/CD are how you work, not a separate DevOps concern.
• 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 the 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, improve.
• You say what you think, including when it is an unpopular take, and 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 you are quick to close the gap.
• You understand financial market data: order books, trades, reference data, portfolios, exposures. Experience with crypto, TradFi, or both is a strong plus.

Nice to have

• Lakehouse experience with Apache Iceberg or Delta Lake.
• Familiarity with DataHub or similar metadata and lineage platforms.
• Rust experience. Some of the 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 the Central Data Team, and the platform, standards, and team culture are yours to shape with us.
• Strong partners across Architecture, Infrastructure, Platform, and the desks themselves. You will not be building data in a vacuum.
• Autonomy on how you work: flexible hours, remote-first, business-hours on-call shared across the team.
• A competitive salary package with various benefits.
• A team that likes each other, with regular online get-togethers and a yearly onsite where everyone is in the same room.

About Keyrock

Keyrock is a market maker and digital asset trading platform founded in 2017. The company trades on more than 80 venues and works with a wide array of asset issuers. Its services span market making, options trading, high-frequency trading, OTC, and DeFi trading desks. With over 250 team members across 42 nationalities working predominantly remotely from hubs in London, Brussels, and Singapore, Keyrock is a pioneer in adopting Rust for algorithmic trading and supports Web3 startups through its Accelerator Program.