Senior Market Data Engineer

• Historical Data Capture and Storage: Design develop and maintain systems for the acquisition storage and retrieval of historical market data from multiple financial exchanges brokers and market data vendors

• Data Integrity and Accuracy: Ensure the integrity and accuracy of historical market data including implementing data validation cleansing and normalization processes.

• Data Architecture Development: Build and optimize data storage solutions ensuring they are scalable high-performance and capable of managing large volumes of time-series data.

• Versioning and Reconciliation: Develop systems for data versioning and reconciliation to ensure that changes in exchange formats or corrections to past data are properly handled.

• Data Source Integration: Implement robust integrations with various market data providers exchanges and proprietary data sources to continuously collect and store historical data.

• Data Access Tools: Build internal tools to provide easy access to historical data for research and analysis ensuring performance ease of use and data integrity

• Collaborate with Trading and Research Teams: Work closely with quantitative researchers and traders to understand their data requirements and optimize the systems for data retrieval and analysis for backtesting and strategy development.

• Performance and Scalability: Develop scalable solutions to handle growing volumes of historical market data including ensuring efficient queries and data retrieval for research and backtesting needs.

• Optimize Storage Costs: Work on optimizing data storage solutions balancing cost-efficiency with performance and ensuring that large datasets are managed effectively.

• Compliance and Auditing: Ensure historical market data systems comply with regulatory requirements and assist in data retention integrity and reporting audits.

Qualifications Required Skills and Experience

• Commercial experience of financial instruments and markets (equities futures options forex etc.) particularly understanding how historical data is used for algorithmic trading.

• Familiarity with market data formats (e.g. MDP ITCH FIX SWIFT proprietary exchange APIs) and market data providers.

• Strong programming skills in Python (Go/Rust is a nice to have)

• Familiarity with ETL (Extract Transform Load) processes (or other data pipeline architecture) and tools to clean normalize and validate large datasets.

• Commercial experience in building and maintaining large-scale time series or historical market data in the financial services industry.

• Strong SQL proficiency: aggregations joins subqueries window functions (first last candle histogram) indexes query planning and optimization.

• Strong problem-solving skills and attention to detail particularly in ensuring data quality and reliability.

• Bachelors degree in Computer Science Engineering or related field.

Preferred Qualifications

• Experience in a proprietary trading firm or buy-side environment working with historical market data and its vendors.

• Experience with data governance and compliance related to financial data storage and retrieval.

• Experience in working with distributed data systems and tools such as Hadoop Kafka Spark or similar technologies.

• Proficiency in containerization orchestration - Docker Airflow SLURM tools.

• Linux/Unix expertise particularly in managing and optimizing systems for data storage and processing.

• Experience with cloud-based storage solutions such as AWS S3 Google Cloud Storage or Azure and the ability to optimize for performance and cost.

• Familiarity with machine learning and data science workflows to support quantitative research teams.

Additional Information What we offer

• Working in a modern international technology company without bureaucracy legacy systems or technical debt.

• Excellent opportunities for professional growth and self-realization.

• We work remotely from anywhere in the world with a flexible schedule.

• We offer compensation for health insurance sports activities and professional training.

Remote Work Yes Employment Type Full-time