Experienced Engineer - Data Upskilling Program

We are seeking an experiencedData Engineer specializing in Data Integration to join our expanding Data Engineering team.

In this role, you will be a key member of one of our established Platform Teams, focusing on robust data integration, ingestion, and pipeline architectures. This is an exciting opportunity to anchor your foundational data engineering skills while actively leveling up your programming and cloud-native expertise.

We offer dedicated upskilling and learning, providing structured opportunities and time to master Python, AI, Databricks, and Cloud, ensuring your technical capabilities grow ahead of the curve.

Responsibilities

• Data Integration & Pipelines: Design, develop, and scale robust data integration workflows, pipelines, and ETL/ELT processes to unify disparate enterprise data sources
• Core Engineering & Optimization: Build and optimize scalable data pipelines and relational data transformations, ensuring high performance, reliability, and data governance
• Architecture & Data Stores: Design cloud-native analytical solutions and maintain modern data lakes and data warehouses
• Active Upskilling & Growth: Dedicate professional time to upskilling and hands-on learning across Python programming, AI technologies, advanced Databricks features, and Cloud platforms (e.g., Microsoft Azure / AWS)
• Collaboration & Quality: Implement data quality, lineage, and monitoring frameworks; collaborate closely with ML, analytics, and AI Factory teams to deliver clean, production-ready datasets
• Technical Leadership: Conduct code reviews, uphold technical standards, mentor junior engineers, and foster a collaborative, high-performance team culture
• CI/CD & DevOps: Integrate CI/CD methodologies into data engineering workflows using tools such as Jenkins, GitLab CI/CD, or GitHub Actions
• Stakeholder Engagement: Engage with stakeholders and architects to understand business processes, model input data, and ensure deliverables meet strategic requirements

Requirements

• 3+ years of experience in Data Engineering, Data Integration, or a related field
• Strong Core Data Engineering Competence: Proven background in data integration patterns, data warehousing, ETL/ELT architecture, and data modeling
• Proficiency in SQL: Strong hands-on experience in SQL for complex data manipulation, querying, and performance tuning
• Python Flexibility: While deep Python experience is not a strict prerequisite, a basic understanding or willingness to learn and master Python is required as part of your upskilling journey
• Cloud & Databricks Familiarity: Hands-on experience or a strong baseline understanding of Cloud services (Microsoft Azure, AWS, or GCP) and Databricks, paired with a clear readiness to master them further
• Growth Mindset & Upskilling Readiness: Highly motivated to dedicate time to upskilling in Python, AI, modern Databricks workloads, and Cloud-native engineering
• Development Practices: Familiarity with software version control (GitHub/Git) and CI/CD frameworks (Jenkins, GitLab CI/CD, Concourse)
• Soft Skills: Strong problem-solving, analytical, and stakeholder communication skills

Nice to have

• Prior experience with Python or PySpark/Spark
• Experience with additional programming languages (Java, Scala)
• Knowledge of enterprise data platforms (such as SAP BTP)
• Familiarity with Agile development methodologies