Director of Data Engineering

Role Overview

• Define and execute the company’s multi-year data strategy, roadmap, and target data architecture.
• Build, scale, and lead high-performing teams across data science, ML engineering, data engineering, analytics, and data governance.
• Establish organisation-wide standards for data quality, consistency, access, and governance.
• Work with product and engineering to enable data driven product decisions and build end-to-end data platform
• Architect scalable, secure, and high-performance data platforms and pipelines.
• Oversee ingestion, modelling, transformation, and orchestration of structured and unstructured data.
• Ensure modern data stack best practices (e.g., warehouse/lakehouse, orchestration, feature stores, catalogues, ML pipelines).
• Optimize and transform data for low latency delivery to client facing applications (web, Excel etc.).
• Lead development, deployment, monitoring, and lifecycle management of ML models.
• Partner with product teams to embed ML features into customer-facing products.
• Enable AI innovation with modern data and machine learning infrastructure.
• Oversee creation of dashboards, metrics frameworks, and analytical tools that empower teams across the business.
• Ensure analytics output is accurate, trustworthy, and tied to business outcomes.
• Partner with finance, sales, and leadership on forecasting, performance analysis, and strategic planning.
• Implement data governance practices including access control, metadata management, and lineage.
• Ensure compliance with relevant regulatory frameworks (GDPR, CCPA, SOC 2, etc.).
• Drive data quality programs with automated monitoring and remediation processes.

Requirements

• Proven experience building, leading, and scaling multi-disciplinary data teams of 10+ members across data engineering, analytics, and machine learning functions.
• Deep expertise in modern data architecture, cloud data platforms, and scalable pipelines.
• Proven leadership experience managing multi-disciplinary data teams.
• Demonstrated success within innovative, product-led technology companies, ideally operating in data-intensive or regulated domains.
• Experience implementing data governance, data quality frameworks, and operational data processes.
• Strong business acumen with ability to translate complex data into strategic, actionable insights.
• Excellent communication skills and ability to influence senior leadership.

Tech Stack

• Cloud

Benefits

• Culture of innovation and collaboration
• Empowerment and continuous learning for team members