Senior Data & Analytics Engineer
J
JobgetherAviation Technology
Based in GermanyFull-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English (C1)
- Experience
- 5+ years
- Required Skills
- SQLGitMicrosoft Power BIAzureSparkDatabricksPySpark
Requirements
- 5+ years of experience in data engineering or analytics engineering, ideally focused on customer-facing BI products.
- Proven experience building scalable data platforms and customer-facing analytics in SaaS or product-driven environments.
- Strong hands-on expertise with Databricks, including Spark/PySpark and Delta Lake.
- Strong experience with Microsoft Fabric and/or the broader Azure data ecosystem.
- Advanced Power BI expertise, including data modelling, DAX, performance optimisation, and semantic models.
- Advanced SQL skills and strong knowledge of dimensional modelling, particularly Kimball methodology.
- Strong understanding of lakehouse architecture, ETL/ELT design, multi-tenant data models, and embedded analytics.
- Experience implementing CI/CD for data pipelines and BI assets, as well as version control using tools such as Git.
- Strong engineering discipline, including writing reusable, modular, maintainable, and testable code.
- Minimum English proficiency of C1.
- Willingness to participate in two annual one-week team events.
Responsibilities
- Take end-to-end ownership of the data platform, including Databricks, Microsoft Fabric, scalable pipelines, and lakehouse architecture.
- Design, build, and operate robust ETL/ELT workflows supporting batch and near-real-time data processing.
- Establish and maintain data quality, reliability, observability, performance, and architectural standards across the platform.
- Own Power BI semantic models, KPIs, dimensional models, DAX performance, aggregations, and dataset refresh processes.
- Build and maintain customer-facing dashboards, embedded analytics, and data exports while ensuring consistent and trusted metrics.
- Enable governed self-service analytics and support secure, scalable multi-tenant data models.
- Translate customer and business needs into scalable data products and define reporting standards.
- Lead the transition from an existing vendor-built BI solution by reverse-engineering logic and rebuilding toward a product-grade architecture.
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