Senior BI Analyst, Reporting & BI

HelloFresh is a global company supporting 6+ million customers with complex supply chain operations. The role is part of the Reporting & BI team responsible for building and maintaining data infrastructure to support executive decision-making.

• 6+ years of experience in BI Analytics, Data Engineering, or Analytics Engineering
• Advanced SQL proficiency and data pipeline experience with complex transformations and performance tuning
• Hands-on experience with modern data stack tools: dbt, Databricks, Spark SQL, and Airflow
• Expertise in data modeling, including dimensional modeling and star schemas
• Proven ability building and maintaining BI dashboards using Tableau, Databricks, or Looker
• Experience in stakeholder management, translating business challenges into analytical work
• Ownership mindset with accountability for data quality and delivery

Nice to have:

• Experience with Python for data transformation and automation
• Familiarity with data monitoring and alerting frameworks such as Great Expectations, Monte Carlo, or dbt tests
• Experience with event-level behavioral data and tracking design tools like Snowplow, Google Analytics, Segment, GA4
• Exposure to statistical modeling techniques including segmentation, clustering, regression, and cohort analysis
• Experience with cloud data platforms: AWS, GCP, Azure, or data migration projects

• Design, develop, and maintain ETL/ELT pipelines using dbt, Databricks, Spark SQL, and Airflow
• Implement automated data quality checks, monitoring, and alerting; troubleshoot pipeline failures
• Write performant, maintainable SQL for large-scale data transformations
• Build and maintain executive-level BI dashboards with Tableau and Databricks
• Conduct deep-dive analyses translating complex business questions into strategic recommendations
• Own critical business reporting including WBRs, QBRs, and forecasting
• Document data models, pipelines, and methodologies to enable self-service
• Mentor junior analysts and engineers on SQL best practices, data modeling, and stakeholder communication