Role Description As a Fullstack Engineer (Semantic / Analytics) (m/f/d), you will own the business meaning of data and make it reusable across analytics, BI, APIs, semantic access, and AI-powered experiences. You will work across semantic modeling, KPI logic, reusable data models, business-facing data exposure, and collaborate closely with platform, AI, solution, and business teams. The platform will continue to evolve toward broader support for unstructured data and lakehouse-style capabilities. We work spec-driven, use AI-assisted engineering tools such as Claude Code and Cursor, follow “You build it, you run it”, and expect strong specialization combined with fullstack ownership. - Build the semantic foundation for data products - Build and evolve the semantic layer in dbt and Snowflake semantic views, including business entities, metrics, dimensions, and reusable data models - Define KPIs, business logic, canonical data definitions, and semantic consistency standards together with business and product stakeholders - Help shape how semantic data products are exposed consistently across internal and external platform capabilities - Ensure business entities, KPIs, and metrics are clearly and consistently defined across the platform - Make curated data usable across BI, APIs, and AI - Expose curated data for BI tools such as Amazon QuickSight and Apache Superset, APIs, downstream product use cases, and AI consumption including Snowflake Cortex AI - Support AI use cases through feature shaping, context structuring, semantic enrichment, and business-grounded data preparation - Collaborate with the AI Engineer to ensure agentic experiences are grounded in meaningful, well-structured business data - Help ensure BI, APIs, and AI use cases rely on the same trusted semantic foundations in Snowflake - Work with reliable, fresh, and governed data - Work with near-real-time data ingested from PostgreSQL into Snowflake via Snowflake Openflow - Ensure semantic models reflect fresh, reliable data from operational systems - Align with solution teams on data contracts, source semantics, and integration expectations - Help define validation rules, data trust practices, lineage support, and consistency controls - Collaborate across platform, product, and engineering - Work closely with the Data & Platform Architect and Data & Platform Engineer to build semantic models on reliable, scalable Snowflake foundations - Collaborate with platform, AI, solution, product, and business-facing teams - Help the company build a reusable semantic layer that scales with future platform growth - Apply spec-driven development, AI-assisted engineering workflows, and end-to-end production ownership Qualifications - Very strong hands-on SQL skills and broad, deep database knowledge, including data modeling - Strong hands-on experience with Snowflake, including Snowflake semantic views - Hands-on experience with dbt at scale for transformations and analytics engineering best practices - Experience with PostgreSQL as a source for structured business data - Experience building semantic layers, reusable metrics, canonical data models, analytics engineering assets, KPIs, business logic, and data definitions with stakeholders - Experience exposing data for BI, APIs, downstream product use cases, and AI or analytics consumption - Experience defining or supporting data contracts, validation rules, semantic consistency standards, data quality, lineage, and trust practices Requirements - Experience with near-real-time or CDC ingestion, ideally Snowflake Openflow or comparable tools such as Fivetran, Debezium, or Kafka - Strong Python skills - Experience building APIs and services such as REST or GraphQL - Experience exposing data and tools through interfaces such as MCP servers - Solid AWS stack know-how - Experience with BI tools such as Amazon QuickSight, Apache Superset, Looker, Tableau, Power BI, or similar platforms - Strong understanding of how data should be structured for AI, analytics, semantic access, and product consumption - Comfortable with structured, spec-driven delivery and AI-assisted development workflows Benefits - 30 days of paid vacation - EGYM Wellpass membership to support your work-life balance - Flexible working models to better balance work and personal life - Inspiring office spaces in the heart of Munich - Flexible remote work from home or anywhere within Germany - A professional, welcoming, and highly motivated team - Collaboration at eye level with an open feedback culture - An environment where people support each other and grow together - Short decision-making paths and real opportunities to shape things - Freedom to contribute and implement your own ideas - A high level of ownership and responsibility