Data Engineering & Analytics Tech Lead
PermanentJob Overview
Lead the design, delivery, and operations of high-impact data and analytics solutions for an innovative healthcare client. You’ll manage a team of data engineers, analysts, and scientists, driving innovation in data infrastructure, tools, and reporting. This role blends strategic vision with hands-on technical leadership, fostering collaboration, mentoring talent, and ensuring best-in-class data products that support healthcare business goals.
Key Responsibilities
- Partner with the Group Chief Data Officer to shape and execute the company's Data Strategy, aligning with business goals and driving data-informed decision-making
- Work cross-functionally to uncover business challenges and translate them into actionable insights through analytics
- Implement and uphold Data Ops best practices to ensure reliable, high-quality data availability
- Manage and document optimized data pipelines, reporting tables, storage solutions, and model deployments
- Manage and maintain data infrastructure including Azure, dbt, Microsoft Fabric, and related ETL/ELT, ML/AI, and storage tools
- Advance Data Science and ML/AI Ops capabilities, guiding use case development, model deployment, and pipeline optimization
- Maintain centralized documentation and code repositories for all data solutions
- Collaborate with product owners to prioritize sprint features and manage technical requirements
- Ensure ongoing compliance with data governance, security, and architectural standards
- Lead a high-performing team of data engineers, analysts, and scientists
- Provide mentorship, guidance, and feedback to foster a collaborative and growth-oriented culture
Skills, Knowledge and Expertise
- 5+ years’ experience in senior data engineering or similar roles within fast-paced, data-driven environments
- Advanced degree (Master’s/PhD) in Science, Engineering, Computer Science, or quantitative field
- Technical background with expertise in data engineering, machine learning, statistics, Data/ML Ops and analytics
- Proficient in SQL, Python, PySpark, and R
- Deep experience with modern data platforms including Azure, Microsoft Fabric, Databricks, dbt, and Power BI
- Proven track record delivering solutions across cloud, on-prem, and distributed systems