Head of Data

About the Role

We are seeking a Head of Data to lead the strategic direction and operational excellence of the firm’s trading data ecosystem. This role will be pivotal in ensuring the quality, reliability, and scalability of data that underpins trading, quantitative research, risk management, and decision-support functions.

Responsibilities

• Define and execute a data strategy focused on trading and market data, ensuring accuracy, timeliness, and integrity.
• Collaborate with the Architecture Team to build a robust and compliant data architecture.
• Drive the organization’s data excellence agenda, embedding reliability and observability across the data platform.
• Lead the implementation and evolution of cloud-native data platforms for trading and financial datasets.
• Standardize data ingestion and modelling patterns to ensure interoperability between systems.
• Enforce and maintain robust data governance across the full lifecycle, including data lineage, access control, and retention.
• Partner with Security and Compliance teams to ensure adherence to SOC 2, ISO/IEC 27001, DORA, and other relevant frameworks.
• Build, lead, and mentor a high-performing Central Data Team (Data Engineering, Data Intelligence, Data Operation).
• Partner with Engineering, Architecture, Quant Research, Risk, and Finance to deliver unified, trusted, and scalable data solutions.
• Define measurable data KPIs around latency, availability, and quality to continuously improve the data platform.

Requirements

• 10+ years of experience in data engineering, data architecture, or data platform leadership roles.
• Proven experience in building and managing trading or financial data platforms.
• Strong understanding of market data feeds, trade lifecycle, and financial data models.
• Expertise with modern data technologies (ClickHouse, PostgreSQL, Kafka, or equivalents).
• Experience implementing ML Ops frameworks (e.g., MLflow, Kubeflow, Prefect, or SageMaker).
• Deep understanding of ETL/ELT pipelines, streaming architectures, and data lifecycle management.
• Experience working in Kubernetes and cloud-native environments (AWS preferred).
• Sound knowledge of data governance, security, and compliance best practices.
• Demonstrated ability to lead cross-functional teams and influence data-driven decision-making.

Nice-to-Haves

• Background in crypto markets, financial trading, or quantitative research environments.
• Exposure to real-time analytics, monitoring, and observability tools (Grafana, Prometheus, DataDog etc.).
• Understanding of DataOps, FinOps, and cost-optimized data management practices.
• Familiarity with distributed systems and high-throughput data processing (e.g., Ray, Dask, Spark).
• Experience with feature engineering, model lifecycle management, and data-driven research environments (e.g., JupyterHub).