A1X Trading
Senior Market Data Engineer (kdb+/Python)
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Senior Market Data Engineer — kdb+/Python
About A1X
A1X is a principal trading firm active in digital-asset derivatives. We combine systematic research, quantitative modelling, and precision in execution to deliver consistent performance across market cycles. Founded by a Bitcoin derivatives trader active since 2012 and built by a team of quantitative researchers and engineers, A1X combines the agility of a proprietary desk with institutional discipline.
The Role
We’re seeking a Senior Data Engineer to join our engineering team and play a key role in our systematic options trading operation. You will be responsible for designing and building the market data platform that underpins quantitative research and trading. You will develop high-performance kdb+/q and Python systems to ingest, validate, store and serve large-scale financial market data while working closely with quantitative researchers, traders and engineers.
Location
UK or Remote (European Timezone)
Responsibilities
- Ingest market data from multiple sources into a validated time series database for quantitative research.
- Design, maintain and optimise kdb+ infrastructure to support growing research and trading workloads.
- Scrub tick-level crypto data, including detecting data gaps, handling duplicate events, aligning timestamps, and filtering bad prints, crossed books, stale levels, invalid quantities and inconsistent state transitions.
- Reconstruct full and depth-limited order books from snapshots and incremental updates, including price-level insertions, modifications and deletions, and produce event-time book states, snapshots and aggregated datasets required by quantitative models.
- Develop and maintain resampled, enriched and derived datasets covering market microstructure, volatility surfaces, term structures, skew, implied volatility, Greeks and risk-model outputs.
- Develop python tooling to support quantitative research, backtesting, data exploration and model development.
- Optimise system performance, including latency analysis, caching and gateway services for scalable access to historical market data.
- Improve data quality through automated validation, monitoring and repair processes.
- Maintain historically accurate instrument reference data and consistent mappings across exchanges and data vendors, including strikes, expiries, option types, contract multipliers and settlement conventions.
- Contribute to disaster recovery planning and infrastructure resilience.
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Requirements
- Minimum 5 years' experience developing kdb+/q and Python systems within financial markets.
- Experience building real-time market-data feed handlers and historical data pipelines.
- Experience reconstructing order books from snapshots and incremental updates.
- Strong understanding of market-data sequence handling, replay, recovery and timestamp semantics.
- Experience handling large-scale, high-frequency time-series datasets.
- Experience with Linux, networking, IPC, memory management and performance profiling.
- Experience with automated testing, CI/CD and production support.
- Ability to work directly with quantitative researchers, traders and trading-system developers.
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Desirable
- PyKX.
- NumPy, Pandas, Polars, Numba, PyArrow or Parquet.
- Cryptocurrency exchange APIs.
- AWS (including S3, EC2, EBS, CloudWatch, IAM, Kinesis).
- Apache Kafka.
- Binary protocols such as SBE or Protobuf.
- Experience with Grafana, monitoring and observability tooling.
- Experience building low-latency market data systems.
- Docker, Kubernetes, Terraform or equivalent deployment tooling.
- Time synchronisation and latency measurement using NTP or PTP.
Benefits & Perks
- Flexible work arrangements.
- Training & Development Budget.
- Comprehensive Health & Dental Insurance.
- Wellness Program.
- Generous Paid Leave.
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