04 ott - Montà
Keyrock
Senior Data EngineerAbout Keyrock Since our beginnings in 2017, we've grown to be a leading change-maker in the digital asset space, renowned for our partnerships and innovation. Se le sue competenze, la sua esperienza e le sue qualifiche corrispondono a quelle descritte in questa panoramica, non ritardi l'invio della sua candidatura. Our diverse team hails from 42 nationalities, with backgrounds ranging from self-taught DeFi natives to PhDs.
Predominantly remote, we have hubs in London, Brussels, and Singapore, and host regular online and offline hangouts to keep the crew tight. As a well-established market maker, our distinctive expertise led us to expand rapidly. Today, our services span market making, options trading, high-frequency trading, OTC, and DeFi trading desks.
We're pioneers in adopting the Rust Development language for our algorithmic trading, and champions of its use in the industry. We support the growth of Web3 startups through our Accelerator Program. And we push the industry's progress with our research and governance initiatives.
We're actively building it.
The Central Data
Team (CDT) is only a few months old, but data has been Keyrock's lifeblood since day one. We're now building the Keyrock Data Platform to give Keyrockers, and the AI agents working alongside them, the data and context they need to act fast and autonomously within agreed boundaries and aligned with our shared goals. Doing that means taking data from across the company and making sense of it in real time for all the functions that depend on it: trading desks, wealth and asset management, product, risk, finance, compliance, and research to name a few.
You'd be one of the early hires in CDT and we expect you to contribute to most of the bigger decisions and build work. 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 us.
Own data contracts and schema evolution. Keep schema changes from turning into multi-team coordination events. Build and evolve the Data Governance and Data Quality Framework: stale-feed detection, schema validation, range checks, idempotent writes, lineage, ownership, 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, performance for wealth and asset management. Treat infrastructure as code (Docker, Terraform, CI/CD) alongside our Central Infrastructure Team.
Work in the open: write things down, partner closely with Architecture, Infrastructure, Platform, and the rest of the teams. Tools matter less to us than how you think about problems.
Engineering
Craft ~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's easy for someone else to read, test, and delete later. ~ Strong understanding of data modelling for both streaming and analytical workloads. ~ Systems Design You've designed and operated streaming systems on Kafka, Redpanda, MSK, or Kinesis, and you have opinions about partitioning, consumer groups, offsets, and schema registries. You've used a time-series store in production (ClickHouse ideally; TimescaleDB, QuestDB, or similar are fine too) and can talk about table design as a function of query patterns. You've worked with a lakehouse architecture and reason about table layout, partitioning,
and compaction as design choices that shape query performance and storage cost.
Reprocessing is safe, retries don't 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" thing.
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 isn't, 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.
A smaller, simpler thing that ships and works beats a bigger thing that doesn't. You say what you think including when it's an unpopular take. You're curious about how markets work. Data engineering on its own won't keep you interested here.
You're honest about what you know and what you don't, and quick to close the gap.
You understand financial market data: order books, trades, reference data, portfolios, exposures. Lakehouse experience with Apache Iceberg or Delta Lake. Familiarity with DataHub or similar metadata/lineage platforms.
Rust. Some of our performance-critical services are written in it. fluency isn't required. You'll be among the first hires in CDT, and the platform, the standards, and the team culture are yours to shape with us.
Close working relationships with Architecture, Infrastructure, Platform, and the desks themselves. You won't 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. Regular online get-togethers and a yearly onsite where everyone's in the same room. The perfect fit? Due to the nature of our business and external requirements, we perform background checks on all potential employees, passing which is a prerequisite to join Key
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