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.