💼 Part-time (2–3 days/week) | Remote | Long-term
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
Scope/impact
• 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.
Must-haves (either track)
• 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).
Azure Fabric track (nice-to-haves become musts if choosing this track):
• Fabric/Synapse pipelines, Lakehouse/OneLake, SQL endpoints.
• Power BI (dataflows, DAX, tabular modeling, Row-Level Security).
• CI/CD for BI (deployment pipelines, versioning, environments).
Open-Source track (nice-to-haves become musts if choosing this track)
• Kafka event streams, Apache NiFi flows (ingest/enrichment/routing).
• dbt (models/tests/docs), ClickHouse for analytics at scale; familiarity with OLAP
engines.
• Apache Superset (dashboards, permissions) and basics of orchestration (e.g., Airflow/Argo) – nice to have.
Cross-cutting pluses
• 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.
Work format: B2B contract, paid days off (holidays, sick leave, public holidays), budget for a laptop.
