AWS Data Engineer

Key Responsibilities: - Design and implement reference/solution architecture for group and corporate data lakes and workflows on AWS (and optionally Google Cloud). - Design user experience of analytics solutions based on business/user context. - Define data engineering and analytics best practices in collaboration with architects. - Serve as consultant/subject matter expert/lead for data engineering and analytics projects as needed. - Contribute to the refresh of the vision, mission, and operating model of the Data and Analytics department. What We're Looking For: - 5+ years progressive experience as an AWS Data Engineer with full‑cycle AWS data lake implementation; experience with Google Cloud Platform/BigQuery preferred. - Functional knowledge in Finance, Procurement, HR, Logistics, or Communications is a clear advantage. - Experience managing projects using agile methodologies with a product focus. - Knowledge of the construction and building materials industry is a plus. - Expert knowledge of AWS data lake services (Redshift, S3, Glue, Athena, DynamoDB, Lambda). - Hands‑on experience with data parsing, cleansing, quality definitions, pipelining, storage, and ETL scripting. - Proficiency in Python, PySpark, and SQL. - Experience consuming REST APIs using various authentication methods within an AWS Lambda architecture. - Ability to orchestrate, debug, and schedule batch jobs using AWS Glue and Lambda. - Understanding of AWS security features such as IAM roles and policies. - Exposure to DevOps tools. - AWS certification highly preferred. - Nice to have: SAP BW and BusinessObjects development experience.