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A fast-growing Swiss-based consulting and technology company specializing in data analytics, AI implementations, and ERP systems is looking for a BI Consultant / Lead to strengthen its team. The company builds intelligent data and analytics solutions for international clients, combining modern cloud technologies with open-source flexibility.
Founded in 2021 and headquartered in Switzerland, it partners with organizations across industries to help them unlock the value of their data — from data integration and modeling to analytics and AI-driven insights.
You’ll join a dynamic environment where experts in Azure Fabric, data engineering, and BI work side by side with business stakeholders to deliver measurable business impact.
We Mainly Run Two Stacks
- Azure Fabric: OneLake/Lakehouse, Fabric/Synapse pipelines, SQL endpoints, Power BI.
- Open-Source: Kafka, Apache NiFi, Iceberg, dbt, ClickHouse, Postgres
- Own the conversation with business, shape the analytics roadmap/KPIs, and define the semantic model.
- Build the critical pieces hands-on or steer our (very capable) data engineering team end-to-end.
- Translate questions into robust data models, data contracts, and reliable dashboards; set QA/governance standards.
- Client-facing BI leadership; ability to frame problems and land simple, valuable solutions.
- Strong SQL and dimensional modelling (star/snowflake); comfortable defining metrics/semantics.
- Backlog writing for engineers (dbt tasks/ELT, data contracts, acceptance criteria).
- Fabric/Synapse pipelines, Lakehouse/OneLake, SQL endpoints.
- Power BI (dataflows, DAX, tabular modeling, Row-Level Security).
- CI/CD for BI (deployment pipelines, versioning, environments).
- Kafka event streams, Apache NiFi flows (ingest/enrichment/routing).
- dbt (models/tests/docs), ClickHouse for analytics at scale; familiarity with OLAP
- Apache Superset (dashboards, permissions) and basics of orchestration (e.g., Airflow/Argo) - nice to have.
- Python for data wrangling; testing (dbt tests, unit/contract tests).
- Data quality & governance (SLAs, monitoring, lineage); GDPR awareness.
- Finance analytics background (P&L, margin, cash, working capital) is a strong plus.
Key Skills
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