Data Engineering Lead

We are seeking a talented Data Engineering Lead to design, develop, and govern our data architecture and pipelines. Join as soon as possible. The candidate will need to be collaborative, organised, think out-of-the-box, and be ready to pursue new opportunities. Most importantly, this role is for an individual who is passionate about making a difference through healthcare.

We have good budget for this position.

• Lead, mentor, and manage a team of data engineers, fostering a culture of technical excellence and continuous improvement.
• Act as a hands‑on technical expert, designing and implementing scalable and robust data architectures for data warehousing and enterprise data platforms.
• Communicate effectively with stakeholders, translating complex business needs into technical requirements and solutions.
• Define and enforce data engineering best practices, including coding standards, documentation, and quality assurance.
• Develop and optimise data pipelines and ETL/ELT/CDC workflows using tools such as Fivetran and Cloud Composer.
• Collaborate with data scientists, product managers, and business stakeholders to define data requirements and create logical and physical data models.
• Manage and administer various database systems, including Big Query, SAP HANA, and PostgreSQL.
• Ensure data quality, integrity, and security across all data platforms and pipelines.
• Work with our AI/ML teams to design data‑serving layers and feature stores that support Vertex AI workloads.
• Design and develop reporting frameworks and data marts to support business intelligence needs.
• Define and implement data governance, master data management, and data cataloguing strategies.
• Contribute to the full data lifecycle: requirements gathering, architecture, data modelling, development, testing, and deployment.
• Troubleshoot and resolve data platform issues to ensure high availability and optimal performance.
• Document technical designs, data lineage, and architecture for cross‑functional reference.

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Science, or a related field.
• Proven experience in a leadership or senior role, mentoring and guiding junior engineers.
• Exceptional communication and interpersonal skills, with the ability to articulate complex technical concepts to diverse audiences.
• Proficiency in one or more backend languages/frameworks, with a strong preference for Python or Go.
• Experience with building RESTful APIs and designing microservices for data delivery.
• Solid grasp of data modelling fundamentals, including Kimball and Inmon methodologies.
• Proficiency in writing complex SQL queries and experience with SQL and No
  
  SQL databases.
• Familiarity with data warehousing concepts and best practices, including CDC.
• Strong version‑control habits (Git) and experience with CI/CD pipelines.
• Excellent problem‑solving and collaboration skills.
• Passion for continuous learning and adapting to emerging data technologies.

• Hands‑on experience designing and deploying production‑grade data warehouses.
• Deep experience with Google Cloud Platform (GCP)
• Big Query for large‑scale analytical workloads.
• Vertex AI for AI/ML model serving and feature stores.
• Experience with other cloud providers (AWS, Azure) and their data services.
• Working knowledge of data governance frameworks, master data management, and data cataloguing tools.
• Experience with data ingestion tools like Fivetran.
• Business‑intelligence expertise in building dashboards and reports with Power BI or Tableau.
• Familiarity with other data technologies such as SAP HANA.
• Understanding of MLOps concepts and their application to data pipelines.
• Contributions to open‑source data projects or technical blogging/presentations.