Global Data Engineer
Unilever is hiring a Global Data Engineer. Level rates it ; you can apply on Unilever.
Level's read on this job
- Little AI ●○○○ is how Level rates this data engineer role: aI is not part of the work.
- Tools and skills the posting cites include Databricks, Google Cloud and SQL.
- Level classifies it as a senior role.
- Level lists 254 other open roles at Unilever.
- The role was posted in the last few days.
AI in this role
Global Data Engineer responsible for designing, building, and operating end-to-end data pipelines and data platforms on GCP and Databricks.
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.
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.
Unilever embraces diversity and encourages applicants from all walks of life! This means giving full and fair consideration to all applicants and continuing development of all employees regardless of age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage and civil partnership, and pregnancy and maternity.
Unilever is an organisation committed to equity, inclusion and diversity to drive our business results and create a better future, every day, for our diverse employees, global consumers, partners, and communities. We believe a diverse workforce allows us to match our growth ambitions and drive inclusion across the business. At Unilever we are interested in every individual bringing their ‘Whole Self’ to work and this includes you! Thus if you require any support or access requirements, we encourage you to advise us at the time of your application so that we can support you through your recruitment journey.
How we rate this
Global Data Engineer at Unilever rates 10 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- Tell me about a project where unity catalog was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Walk me through how you've used Databricks in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Data Engineering, Data Pipelines, Unity Catalog, ETL, and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
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