About the Role

As a Data Engineer on the Data Services & Operations team, you will be the primary point of contact for data requests — connecting business users with the right data assets while upholding governance, security, and service standards. The role is equal parts engineering, stakeholder partnership, and operational excellence.

Key Responsibilities

Data Access & User Enablement

• Triage and coordinate incoming data requests; advise business users on the most suitable datasets for their use case.
• Translate data availability assessments into clear, actionable guidance for non-technical stakeholders.
• Partner with requestors, operations colleagues, and domain data engineers to fulfil approved requests end-to-end.

Data Engineering & Service Delivery

• Build and operate reliable data extraction and delivery pipelines that meet accuracy, security, and SLA requirements.
• Manage recurring data submissions to government partners, from ingestion through compliant delivery.
• Ensure every data service adheres to HPB's governance framework and access control policies.

Data Discovery & Metadata

• Curate and maintain metadata on HPB's data discovery platform so datasets are accurately described and easily found.
• Work with data owners and engineers to lift metadata quality and build a useful, navigable catalogue.
• Continuously refine dataset descriptions, classifications, and catalogue entries.

Support & Continuous Improvement

• Provide Level-1 support via the CDOO service management system — triaging, resolving, and routing as needed.
• Identify and drive process improvements that reduce turnaround time and improve user experience.
• Maintain documentation and knowledge-base content to support team continuity and operational excellence.

Qualifications

• Minimum 2 years (Associate Consultant level) in data engineering, data operations, analytics support, data integration, or metadata management. Public health domain experience is a plus.
• Bachelor's degree in Computer Science, Computer Engineering, Information Systems, Data Analytics, or a related discipline. Alternatively, a Bachelor's in Engineering or Science paired with accredited professional certifications in data engineering, data analytics, or data science and relevant experience.
• SQL and PySpark and/or Python, with hands-on experience working with structured datasets and data transformation pipelines.
• Cloud data platforms — preferably Microsoft Azure, including Databricks and enterprise data warehouse environments.
• Working knowledge of data governance, metadata management, and data catalogue concepts.
• Strong stakeholder management and communication skills.
• Analytical, problem-solving, and service-oriented mindset.
• Process-oriented; able to translate business requirements into data solutions.
• Detail-oriented with a commitment to operational excellence.

Nice to Have:

• Hands-on experience with Microsoft Purview and Unity Catalog.
• Professional certifications in cloud, data engineering, data governance, or analytics.