About the Role:

Join our dynamic Central Europe Backend Engineering team as a Data Engineer with Databricks and play a crucial role in shaping our data landscape! We're seeking a skilled, hands-on expert in Databricks and data engineering to design, develop, and implement robust data pipelines, specifically processing shipment, sell-out, and market share data across Central Europe.

This is a high-impact opportunity to contribute to a significant scope: powering 12+ digital products and serving 700 users across the region. Your work will directly enable insightful analytics, drive data-driven decision-making, and help us continuously innovate and optimize our business strategies.

If you thrive in a fast-paced environment, love solving complex data challenges, and are passionate about building scalable, efficient data solutions, we encourage you to apply!

Key Responsibilities:

As a Databricks Data Engineer, you will:

• Develop Core Data Solutions: Design and develop high-quality code within Databricks (leveraging PySpark notebooks and SQL) to meet specific business requirements, comprising at least 70% of your primary responsibilities.
• Accelerate Development: Utilize existing AI capabilities, such as GitHub Copilot or industry tools like BMAD, to enhance productivity and accelerate development cycles.
• Data Set Assembly: Assemble and prepare large, complex datasets, ensuring they meet critical functional and non-functional business requirements for diverse applications.
• Architectural Collaboration: Partner with data asset managers, architects, and development leads to ensure all technical data solutions are fit for purpose, align with architectural blueprints, and deliver high-quality, reliable data.
• Maintain Standards: Contribute to and actively leverage established coding standards and best practices, ensuring that all services and components are efficient, scalable, and reusable.
• Cross-Functional Partnership: Collaborate effectively with front-end teams, embracing a "data as a product" mindset to ensure seamless data delivery and integration.
• Adhere to Best Practices: Consistently apply sound development practices and adhere to agreed-upon architectural designs throughout the development lifecycle.
• Technical Debt Reduction: Proactively identify and define infrastructure revamp initiatives aimed at reducing technical debt and enhancing system longevity.
• Agile Delivery: As an integral member of a Scrum team, deliver data engineering projects efficiently and in alignment with business priorities and agile methodologies.
• Operational Support: Provide timely L3 support for existing data processes, thoroughly analyzing bugs and incidents to ensure system stability and performance.
• Process Improvement: Identify, design, and implement continuous internal process improvements to streamline and automate backend operations.
• Continuous Learning: Stay abreast of industry trends, emerging technologies, and best practices in data engineering and management, applying this knowledge to drive innovation, foster improvement, and contribute to team-wide knowledge sharing initiatives.

Qualifications:

• PySpark Expertise: Strong proficiency in PySpark for efficient data processing, transformation, and analysis.
• Databricks Proficiency: Proven hands-on experience with Databricks, including cluster management, notebook development, and job scheduling.
• SQL Mastery: Advanced proficiency in SQL for complex data manipulation, querying, and performance tuning.
• Data Pipeline Experience: Solid experience in designing, implementing, and optimizing robust data pipelines and ETL/ELT processes using PySpark and Databricks.
• Data Modeling Knowledge: Familiarity with data modeling, data warehousing concepts, and dimensional modeling techniques.
• Data Architecture Understanding: A clear understanding of data integration patterns, data lake architectures, and best practices for ensuring data quality.
• Workflow Orchestration (Plus): Experience with Databricks Workflow management and the orchestration of data pipelines is a significant advantage.
• Cloud Platform Exposure (Plus): Experience with Google Cloud Platform (GCP) will be considered a plus.

We offer

• P&G-sized projects and access to world leading IT partners and technologies from Day 1.
• Wide range of self-development possibilities (training and certifications paths).
• Competitive starting salary and benefits program (private health care, P&G stock, saving plans, sport cards).
• Regular salary increases and possible promotions - in line with your results and performance.
• Opportunity to change role every few years to be in the best place for you and best for P&G.