Head Of Data, Keyrock

• The successful candidate combines deep technical expertise in data engineering and ML workflows with a strategic mindset and a strong understanding of trading-related data models and compliance 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

Desirable

• 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
• The Head of Data will drive data excellence across the organisation by defining best practices, enhancing data reliability and performance, and enabling teams to derive meaningful insights and value from data
• Define and execute a data strategy focused on trading and market data, ensuring accuracy, timeliness, and integrity across the lifecycle
• Collaborate with the Architecture Team to build a robust and compliant data architecture optimised for analytical workloads, operational systems, and regulatory obligations
• Drive the organisation’s data excellence agenda, embedding reliability and observability across the data platform, while ensuring alignment with established governance standards
• Prioritise initiatives that enhance trading visibility, risk transparency, and business performance through data
• Identify opportunities where data and ML capabilities can enhance trading performance, risk assessment, and business efficiency
• Lead the implementation and evolution of cloud-native data platforms that support ingestion, transformation, and analytics of trading and financial datasets, in close collaboration with the Architecture Team
• Standardise data ingestion and modelling patterns to ensure interoperability between systems
• Collaborate closely with the Architecture Team to align data platform evolution with enterprise and application architecture principles
• Ensure data systems meet performance, cost, and scalability targets across multiple environments
• Drive the adoption of data engineering best practices that balance agility with operational excellence
• 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
• Ensure consistent metadata, documentation, and versioning across the data stack
• Champion a data-driven culture, ensuring transparency, traceability, and auditability of all data assets
• 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
• Foster a culture of data reliability, accountability, and continuous improvement across teams
• Define measurable data KPIs around latency, availability, and quality to continuously improve the data platform
• Promote collaboration between data producers and consumers to streamline trading analytics, reporting, and automation
• Champion a data-driven and experimentation-driven culture across the organisation