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Metro location, popular Data Engineer title, 3–6 years range, and broad Azure/Databricks requirements increase applicant competition.
Core cloud and data engineering skills are transferable, though healthcare governance adds moderate domain bias.
Specific Azure/Databricks, Spark, and 4+ years requirement make technical screening rigorous.
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Develop, integrate, and deliver reusable data solutions on Haleon’s Enterprise Data & Analytics Platform using latest technologies.
Own and ensure timely delivery of complex data engineering projects in partnership with third-party providers and internal teams, maintaining quality and alignment with stakeholder expectations.
Collaborate on technical architecture, maintain governance, and manage risks/issues for platform build and ongoing enhancements.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science or equivalent experience.
4+ years of hands-on data engineering experience with strong coding skills in Python, SQL, Scala.
Experience with Azure data stack (Databricks, Data Factory, SQL DW, Power BI) and enterprise data tools (Ataccama, Talend, Collibra, Snowflake).
Proven experience delivering enterprise-scale analytics solutions using Agile methodologies (SAFe, Jira, Azure DevOps).
Proficient in big-data processing concepts, schema-on-read, with deep knowledge of Spark, Databricks, and Delta Lake addressing data science/machine learning needs.
Experienced in collaborating cross-functionally with IT security, compliance, infrastructure, and business stakeholders to deliver analytic solutions.
Skilled at communicating complex technical concepts to non-technical audience and managing external technology partners to build flexible platforms.