The Global Data & AI department is on a mission to turn DB Schenker into a data-driven company. Our Data Engineering team focuses on designing advanced analytics solutions to solve potential business use cases in logistics using Machine Learning, AI techniques, Data Visualization tools and Big Data technologies in cooperation with our Software Engineering team, internal business units and global IT. We are looking for a talented Data Engineer who can contribute to our projects with solid data intuition, hands-on problem-solving skills, engineering mindset and eagerness to learn about our logistics business data.
Your tasks:
- Support to existing Data capture solution and be an active Development member of migration to new technology.
- Analyze data and design, code, test, debug, automate, document, and maintain data solutions for multiple platforms.
- Support in DevOps implementation.
- Support in optimizing release process which include shell scripting, automation thought process.
Requirements:
- Proactive DevOps automation mindset.
- Relevant experience in release process, Shakedown, POSIX systems (e.g., Linux) and the command-line terminals.
- Relevant experience knowledge in Oracle Golden Gate, Oracle DB (AWS-RDS) and its automation.
- Experience with relational databases (Oracle, PostgreSQL, Snowflake) and knowledge of SQL.
- Experience in creation of task and monitoring dashboard of the platforms like OGG, Qlik-Replicate, Oracle etc.
- Experience in delivering end to end release management & development life cycle: source code repositories (Git) and versioning/branching/peer reviewing, continuous integration (e.g., GitLab CI/Azure DevOps, Jenkins), deployment/release (e.g., artifact building and repositories), maintenance.
- Experience in at least one programming language such as Python.
- Documentation is an important part of this role.
- Business level English
Nice-to-have knowledge:
- Experience with processes (data versioning, model versioning)
- Familiarity with Cloud Data Warehouse and/or Data Lakehouse Approaches
- Experience in Metadata Management
