Job Location WARSAW DOWNTOWN OFFICE Job Description SENIOR DATA ENGINEER (Data & Analytics) – WARSAW, SKYLINER office Senior Data Engineer in Databridge EU team Join us to lead the evolution of Data & Analytics products used by over 2,000 users across Europe. You will own the design, delivery, and optimization of our next-generation data platform, driving infrastructure cost efficiency, advanced analytics capabilities, and productivity gains across European IT and A&I. What you’ll own and build Architect and implement highly scalable, automation-first data pipelines and services using Python, SQL, and Spark with strong emphasis on reliability and performance Lead data modeling initiatives for complex BI scenarios, including advanced partitioning strategies and incremental refresh Drive automation and standardization by developing reusable code templates, job configurations, and infrastructure-as-code components to reduce maintenance overhead Champion AI-assisted development workflows, leveraging GenAI tools to accelerate coding, testing, and documentation while ensuring quality and maintainability Take full ownership of code quality, conducting thorough design and code reviews, and guiding architectural decisions on data platform components Define and enforce engineering standards spanning version control, CI/CD pipelines, testing frameworks, and documentation best practices Collaborate deeply with cross-functional stakeholders and scrum teams throughout the product lifecycle, ensuring delivery excellence and technical alignment Tech you’ll master and influence Advanced Python, SQL, and Apache Spark development Git-based workflows, CI/CD automation (GitHub Actions, Azure DevOps), and shell/PowerShell scripting Modern cloud-native data ecosystems (Databricks, Azure Data Services) with a focus on cost-effectiveness and scalability GenAI-driven developer productivity tools (e.g., GitHub Copilot) for enhanced software craftsmanship What you bring Deep expertise in SQL and Python with proven ability to optimize complex, large-scale data workflows Strong command of data modeling principles tailored for analytics—dimensional models, partitioning, and performance tuning Mastery of Spark for building robust ETL pipelines in cloud environments Experience architecting and managing comprehensive CI/CD pipelines and automation tooling for data engineering Demonstrated leadership in code reviews, documentation standards, and cross-team knowledge sharing Excellent communication skills, with a collaborative approach and ability to influence across multidisciplinary teams Nice to have (optional but highly valued) Hands-on experience with Databricks platform specifics, including job template parametrization Background in query optimization techniques and data pipeline debugging at scale Strong Agile/Scrum mindset with cross-team coordination experience Exposure to cutting-edge GenAI tools beyond basic coding assistance Power BI at scale, including DAX optimization and star/snowflake schema design Why this role?
Eligibility / Qualification Required:
What you’ll own and build Architect and implement highly scalable, automation-first data pipelines and services using Python, SQL, and Spark with strong emphasis on reliability and performance Lead data modeling initiatives for complex BI scenarios, including advanced partitioning strategies and incremental refresh Drive automation and standardization by developing reusable code templates, job configurations, and infrastructure-as-code components to reduce maintenance overhead Champion AI-assisted development workflows, leveraging GenAI tools to accelerate coding, testing, and documentation while ensuring quality and maintainability Take full ownership of code quality, conducting thorough design and code reviews, and guiding architectural decisions on data platform components Define and enforce engineering standards spanning version control, CI/CD pipelines, testing frameworks, and documentation best practices Collaborate deeply with cross-functional stakeholders and scrum teams throughout the product lifecycle, ensuring delivery excellence and technical alignment Tech you’ll master and influence Advanced Python, SQL, and Apache Spark development Git-based workflows, CI/CD automation (GitHub Actions, Azure DevOps), and shell/PowerShell scripting Modern cloud-native data ecosystems (Databricks, Azure Data Services) with a focus on cost-effectiveness and scalability GenAI-driven developer productivity tools (e.g., GitHub Copilot) for enhanced software craftsmanship What you bring Deep expertise in SQL and Python with proven ability to optimize complex, large-scale data workflows Strong command of data modeling principles tailored for analytics—dimensional models, partitioning, and performance tuning Mastery of Spark for building robust ETL pipelines in cloud environments Experience architecting and managing comprehensive CI/CD pipelines and automation tooling for data engineering Demonstrated leadership in code reviews, documentation standards, and cross-team knowledge sharing Excellent communication skills, with a collaborative approach and ability to influence across multidisciplinary teams Nice to have (optional but highly valued) Hands-on experience with Databricks platform specifics, including job template parametrization Background in query optimization techniques and data pipeline debugging at scale Strong Agile/Scrum mindset with cross-team coordination experience Exposure to cutting-edge GenAI tools beyond basic coding assistance Power BI at scale, including DAX optimization and star/snowflake schema design Why this role? Take ownership of a flagship data platform shaping BI and ML capabilities across Europe Lead the adoption of modern, AI-augmented, automation-first engineering practices Grow your technical leadership in a challenging environment with senior peers and mentorship opportunities Deliver impactful solutions that become organizational standards and blueprints Job Qualifications Deep expertise in SQL and Python with proven ability to optimize complex, large-scale data workflows Strong command of data modeling principles tailored for analytics—dimensional models, partitioning, and performance tuning Mastery of Spark for building robust ETL pipelines in cloud environments Experience architecting and managing comprehensive CI/CD pipelines and automation tooling for data engineering Demonstrated leadership in code reviews, documentation standards, and cross-team knowledge sharing Excellent communication skills, with a collaborative approach and ability to influence across multidisciplinary teams We offer P&G-sized projects and access to world leading IT partners and technologies from Day 1.
How to Apply:
Apply online through the official P&G careers portal.
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