Role summary
HelloFresh is seeking a Senior BI Analyst to own their data landscape, building and maintaining the infrastructure for executive decision-making. This role involves creating data pipelines, ETL/ELT jobs, executive dashboards, and conducting deep-dive analyses. The ideal candidate combines analytical depth with engineering capabilities, translating ambiguous business questions into actionable insights and driving end-to-end delivery from raw data to strategic recommendations. Responsibilities include developing and maintaining ETL/ELT pipelines using dbt, Databricks, Spark SQL, and Airflow, implementing data quality checks, writing performant SQL, building BI dashboards in Tableau and Databricks, and partnering with Product, Marketing, Finance, and Operations teams. The role requires 6+ years of experience in BI Analytics, Data Engineering, or Analytics Engineering, with advanced SQL proficiency and experience with modern data stack tools.
The Role
As a Senior BI Analyst in the Reporting & BI team, you will be the owner of HelloFresh's data landscape for your domain. You will build and maintain the data infrastructure that powers executive decision-making — from creating data pipelines and ETL jobs to building executive-level dashboards and conducting deep-dive analyses.
You combine analytical depth with engineering capabilities: translating ambiguous business questions into actionable insights and own end-to-end delivery — from raw data ingestion through transformation pipelines to polished dashboards and strategic recommendations that reach C-suite stakeholders.
This role is ideal for someone who thrives at building things: pipelines, data models, dashboards, and insights — all while ensuring data quality, scalability, and business impact.
What You'll Do: The Recipe
Design, develop, and maintain ETL/ELT pipelines using dbt, Databricks, Spark SQL, and Airflow — transforming raw data into robust, scalable models that power analytics across the business
Act as the steward of your domain's data landscape: implement automated data quality checks, monitoring, and alerting to proactively catch issues, and troubleshoot pipeline failures with timely root-cause fixes
Write performant, maintainable SQL for large-scale data transformations and collaborate with central Data Engineering teams on schema design and technical requirements
Build and maintain executive-level BI dashboards (Tableau, Databricks) and conduct deep-dive analyses that translate complex, ambiguous business questions into data-driven strategic recommendations
Own critical business reporting (WBRs, QBRs, forecasting) and act as the trusted analytics partner across Product, Marketing, Finance, and Operations — ensuring insights are accurate, timely, and actionable
Document data models, pipelines, and methodologies to enable self-service, and mentor junior analysts and engineers on SQL best practices, data modeling, and stakeholder communication What You'll Bring: The Ingredients
6+ years of experience in BI Analytics, Data Engineering, or Analytics Engineering — ideally in a fast-paced B2C, subscription, or growth-oriented business
Advanced SQL proficiency and data pipeline experience — comfortable with complex transformations, performance-tuning, and building/troubleshooting ETL/ELT pipelines at scale
Modern data stack tools — hands-on experience with dbt, Databricks, Spark SQL, Airflow, or similar orchestration and transformation tools
Data modeling expertise — strong understanding of dimensional modeling, star schemas, and designing scalable data models
Proven ability to build and maintain BI dashboards (Tableau, Databricks, Looker, or similar) that reach senior leadership
Stakeholder management — experience translating ambiguous business challenges into structured analytical work and influencing cross-functional partners (Product, Marketing, Finance, Operations)
Ownership mindset — proactively identifies issues, drives solutions, and takes accountability for data quality and delivery Nice to Have:
Python for data transformation, ad-hoc analysis, automation, or lightweight modeling
Experience with data monitoring and alerting frameworks (Great Expectations, Monte Carlo, dbt tests)
Experience with event-level behavioral data and tracking design (Snowplow, Google Analytics, Segment, GA4) — schema design, entity modeling, event naming
Exposure to statistical modeling techniques — segmentation, clustering, regression, cohort analysis
Experience with cloud data platforms (AWS, GCP, Azure) or data migration projects. What we offer: The Toppings
Global collaboration at scale: Collaborate with experienced engineers and product partners across HelloTech’s international teams, in a culture of active knowledge sharing.
Technology with real-world impact: Build and operate modern systems at a global scale, supporting 6+ million customers and complex supply chain operations.
Technical/Product/Design leadership: Drive best practices and influence architecture/design, quality, and ways of working in an autonomous, product-led setup.
End-to-end development/delivery: Drive decisions from problem definition to production, improving systems and enabling long-term scalability.
Access to the workspace at Warsaw Centre Point. The hub offers modern facilities including showers, breakout zones, outdoor space, cycle parking, and refreshments (coffee, soft drinks, and fruit). Are you the missing ingredient? If this sounds like a tasty opportunity, we’d be excited to hear from you. We aim to review your profile and respond within 5 business days.
#Data
Data Analytics & BI AnalystCoVet · Remote · Remote
