Data Engineer for Shelf Analytics MŁ
Posted 1 day 5 hours ago by Luxoft
We are looking for an experienced Data Engineer to join the Shelf Analytics project - a data-driven application designed to analyze how P&G products are positioned on store shelves. The primary objective of the solution is to improve product visibility, optimize in-store execution, and ultimately increase sales by combining shelf layout data with sales insights. As a Data Engineer, you will play a key role in building, maintaining, and enhancing scalable data pipelines and analytics workflows that power shelf-level insights. You will work closely with analytics and business stakeholders to ensure high-quality, reliable, and performant data solutions.
Responsibilities- Design, develop, and maintain data pipelines and workflows using Databricks and PySpark
- Read, understand, and extend existing codebases; independently develop new components for Databricks workflows
- Implement object-oriented Python solutions (classes, inheritance, reusable modules)
- Develop and maintain unit tests to ensure code quality and reliability
- Work with Spark SQL and SQL Server Management Studio to create and optimize complex queries
- Create and manage Databricks workflows, clusters, databases, and tables
- Handle data storage and access management in Azure Data Lake Storage (ADLS), including ACL permissions
- Collaborate using GitHub, following CI/CD best practices and working with GitHub Actions
- Support continuous improvement of data engineering standards, performance, and scalability
- Strong programming skills in Python and PySpark
- Hands-on experience with Databricks (workflows, clusters, tables, databases)
- Solid knowledge of SQL and experience with Spark SQL and SQL Server Management Studio
- Experience with pandas, dbx, and unit testing frameworks
- Practical experience working with Azure Storage (ADLS) and access control (ACLs)
- Proficiency with GitHub, including CI/CD pipelines and GitHub Actions
- Ability to work independently, analyze existing solutions, and propose improvements
Experience with retail, CPG, or shelf analytics-related solutions
Familiarity with large-scale data processing and analytics platforms
Strong communication skills and a proactive, problem-solving mindset