Senior Data Engineer

CMC Markets; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

CMC Markets is seeking a Senior Data Engineer to build and operate a high-performance market data platform supporting quantitative research and production trading systems. You will design scalable data pipelines, process billions of market data records, and deliver reliable, production-quality datasets for research, analytics and real-time applications.

The role requires expert Python and SQL, experience with distributed processing, and familiarity with modern storage formats like Parquet.

Qualifications

• Expert Python and SQL.
• Automated data quality controls.
• Deep tick and market data expertise.
• Experience with distributed processing (Spark, Polars, Dask, Ray or similar).
• Experience with Kafka or similar streaming technologies.
• Familiarity with PostgreSQL, ClickHouse, Snowflake, Databricks, kdb+ or similar.
• Docker, Linux, Git and CI/CD experience.

Responsibilities

• Build scalable ETL/ELT pipelines for batch and streaming market data.
• Develop production-grade Python and SQL solutions.
• Ingest, normalise and validate market data, including trades, ticks, Level 1 & 2 quotes, order books, reference data and corporate actions.
• Implement automated data quality, reconciliation and monitoring frameworks.
• Optimise data storage using Parquet, Arrow and modern data lake technologies.
• Partner with quantitative researchers, traders and engineering teams to deliver trusted datasets.

Skills

Python

SQL

Data pipelines

Data quality

Time-series data

Distributed processing

Kafka

Docker

Linux

Git/CI-CD

Tools

Spark

Polars

Dask

Ray

Parquet

Arrow

PostgreSQL

ClickHouse

Snowflake

Databricks

kdb+

Job description

We are looking for a Senior Data Engineer to build and operate a high-performance market data platform supporting quantitative research and production trading systems. You'll design scalable data pipelines, process billions of market data records, and deliver reliable, production-quality datasets for research, analytics and real-time applications.

Key Responsibilities

• Build scalable ETL/ELT pipelines for batch and streaming market data.
• Develop production-grade Python and SQL solutions.
• Ingest, normalise and validate market data, including trades, ticks, Level 1 & 2 quotes, order books, reference data and corporate actions.
• Implement automated data quality, reconciliation and monitoring frameworks.
• Optimise data storage using Parquet, Arrow and modern data lake technologies.
• Partner with quantitative researchers, traders and engineering teams to deliver trusted datasets.
• Strong Python and SQL.
• Expertise with Parquet and modern data storage formats.
• Deep understanding of high-frequency market data, including tick data, order books and market data normalisation.
• Experience handling time-series challenges such as timestamp precision, sequence gaps, duplicate and out-of-order events.
• Experience with distributed processing (Spark, Polars, Dask, Ray or similar).
• Experience with Kafka or similar streaming technologies.
• Familiarity with PostgreSQL, ClickHouse, Snowflake, Databricks, kdb+ or similar.
• Docker, Linux, Git and CI/CD experience.

Highly Desirable

• Familiarity with OneTick, PostgreSQL, ClickHouse, Snowflake, Databricks, kdb+ or similar.
• Order book reconstruction
• Airflow, Dagster, Prefect or MLflow
• Experience supporting quantitative research or trading systems

What We're Looking For

The successful candidate will have a strong background in market data engineering with proven experience building reliable, scalable data platforms.

Our non-negotiable requirements are:

• Expert Python
• Strong SQL
• Automated data quality controls
• Deep tick and market data expertise

Experience in MLOps is advantageous but not essential. We welcome candidates with strong experience in either market data engineering or MLOps, provided they have the skills to build and operate production-grade data platforms.