The role involves designing, building, and maintaining scalable ingestion pipelines within a Medallion architecture. The professional will model and transform business data to support operational reporting while ensuring data quality through automated checks and reconciliation processes. Responsibilities include implementing governed data access controls to meet privacy compliance obligations and documenting platform tables in a data dictionary. The individual will collaborate with architects and stakeholders to align designs with enterprise standards and produce technical runbooks for internal teams. Additionally, the position supports the deployment of solutions across development, testing, and production environments.

Candidates must possess at least five years of experience in data engineering within cloud-based analytical environments. Required technical proficiencies include SQL, Python, and experience with Azure data services such as Data Factory and Data Lake Storage. Applicants need hands-on experience with modern cloud data warehousing platforms like Databricks or Snowflake, specifically regarding layered architectures. Furthermore, the role requires an understanding of data governance, access controls, and privacy compliance, alongside familiarity with Git-based CI/CD workflows and strong communication skills. Advanced English proficiency is mandatory.