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Data & AI Senior Engineer
Skills
Computer ScienceApache SparkCFRContinuous ImprovementData ServicesData StrategiesEvolution
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- Bachelor's degree in Computer Science Data Engineering or related technical field or equivalent experience
- 4 to 6 years of experience in data engineering software development or data architecture
- Advanced proficiency in Python and SQL
- Deep experience with distributed data processing such as Spark and modern lakehouse architectures such as Databricks
- Experience integrating SAP data platforms and virtualization technologies into enterprise solutions
- Strong understanding of data quality observability and performance optimization
- Ability to lead teams through technical challenges while remaining hands-on in design and coding
- Experience working within agile product teams and coordinating across multiple stakeholders
- Strong understanding of API-first and event-driven architecture patterns with secure service-to-service communication and RBAC
- Experience embedding data quality validation schema enforcement lineage tracking and policy-as-code controls into pipelines and AI workflows
- Excellent communication collaboration and problem-solving abilities
- Experience building reusable cost effective feature stores semantic layers or internal platform services
Nice to have
- Leadership capacity
- Scaled agile experience
- Mentorship experience
- Technical leadership
Day to day
- Lead the design and delivery of scalable data and AI solutions across Databricks SAP data environments and virtualization layers to support trusted enterprise decision-making
- Build and optimize pipelines integrations and data services with strong attention to performance security governance and reusability
- Mentor junior and mid-level engineers while influencing technical standards and collaborating with architects product owners and governance leaders