Data Engineer for trade promotion analytics

Procter & Gamble produces globally recognized consumer brands and serves consumers worldwide. Its portfolio includes brands such as Always, Ariel, Gillette, Head & Shoulders, Oral-B, and Pampers, with operations in approximately 70 countries.

• Design, build, test, and deploy automated data pipelines and ETL/ELT processes on Azure and Databricks
• Write clean, maintainable, production-ready Python and PySpark code for data transformations, integrations, and aggregations
• Develop, tune, and optimize complex SQL queries for high performance and efficient pipeline execution
• Ensure end-to-end data quality, consistency, and reliability across production data flows
• Design and implement a harmonized relational and analytical data model as a single source of truth for downstream analytics
• Analyze multi-source data models and schemas, including data flows, entity relationships, constraints, and business logic
• Collaborate with Data Analysts and business stakeholders to translate analytical requirements into scalable data structures
• Ensure consistent data modeling practices and maintain architectural documentation across data assets
• Act as the technical point of contact, subject matter expert, and quality gatekeeper for external vendor deliverables
• Review code and approve pull requests to ensure compliance with coding, testing, and security standards
• Partner with the Product Owner to track delivery milestones, technical trade-offs, and early mitigation of technical debt
• Promote engineering best practices, CI/CD, and shared team standards

• Experience conducting code reviews, establishing best practices, and providing technical guidance to junior peers or external vendor developers
• Strong communication skills and ability to explain technical trade-offs to project stakeholders
• Expert-level understanding and hands-on experience with relational data modeling, data warehousing concepts, and database design
• Expert-level SQL proficiency, including complex queries, performance tuning, and advanced functions across database systems
• Advanced Python programming skills for data manipulation, including Pandas
• Hands-on experience developing PySpark solutions in distributed computing environments
• Practical experience with the Azure data stack, including Azure Data Lake Storage, Azure Data Factory, or Synapse Analytics, and Databricks
• Strong analytical, problem-solving, and critical-thinking skills, including the ability to break down complex business and data problems

• Competitive starting salary and benefits, including private health care, P&G stock, saving plans, and sport cards
• Regular salary increases and possible promotions based on results and performance
• Training and certification opportunities
• Role-change opportunities every few years
• Hybrid work model with the option to work from home two days a week
• Employment exclusively under an “Umowa o Pracę” full-time employment contract; apply only if you agree to these conditions