Global Data Engineer

About Unilever With 3.4 billion people in over 190 countries using our products every day, Unilever is a business that makes a real impact on the world. Work on brands that are loved and improve the lives of our consumers and the communities around us. We are driven by our purpose: to make sustainable living commonplace, and it is our belief that doing business the right way drives superior performance. At the heart of what we do is our people we believe that when our people work with purpose, we will create a better business and a better world. At Unilever, your career will be a unique journey, grounded in our inclusive, collaborative, and flexible working environment. We don t believe in the one size fits all approach and instead we will equip you with the tools you need to shape your own future. Job Purpose The Ops Excellence Global Data Engineer owns the end-to-end data platform that powers global operational reporting, including the PEX data product, the Product Data Store (PDS) and the OPTICS 4-Layer Reporting Framework (Engage, Perform, Manage). The role is accountable for building, running and governing reliable, secure and cost-efficient data pipelines on GCP and Databricks, from source ingestion through to the Power BI frontend. The position combines data engineering, platform operations and product ownership: ensuring pipelines run on time, data is accurate, releases are controlled, the platform is compliant with Unilever architecture and security standards, and the solution is ready to scale for future reporting and data democratization needs across global hubs and markets. What Will Your Main Responsibilities Be A. Data Platform Engineering & Pipeline Development Design, build and maintain scalable data pipelines on GCP and Databricks (SQL, PySpark) feeding the PEX data product, PDS and OPTICS reporting layers. Develop and manage data assets in Unity Catalog, including schemas, tables, lineage and access policies. Manage storage and security components across GCS (Google Cloud Storage), IAM (Identity & Access Management) and Secret Manager. Build and operate pipeline orchestration through the applicable target-state framework, such as Managed Airflow / Cloud Composer, Orion, Databricks Workflows or GCP Workflows. Apply Data Lake and Product Data Store architecture principles to ensure a structured, reusable and well-modelled data layer. B. End-to-End Platform Support & Operations Own pipeline execution, scheduling, monitoring, reruns and failure resolution to guarantee timely and complete data delivery. Maintain Databricks notebooks, workflows and clusters, including Databricks Runtime (DBR) and LTS version upgrades. Manage Incidents and Service Requests end to end, including triage, root-cause analysis, resolution and stakeholder communication.

Desired Candidate Profile

What You Need To Succeed Experiences & Qualifications Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field. 3-5 years of hands-on data engineering experience supporting production cloud pipelines, ideally on GCP with Databricks. End-to-end ownership experience spanning ingestion, transformation, governance, and reporting. Strong knowledge of ETL/ELT, data quality, data governance, security, and enterprise IT controls. Power Automate, Power Platform, and SharePoint exposure is an advantage.