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FlixBus is seeking a Senior Analytics Engineer to own and evolve the data foundation behind People Analytics. You will join an established People Analytics environment with significant opportunity to shape the future direction, moving from traditional reporting toward automated and AI-enabled data workflows.
In this role, you will sit at the intersection of data engineering and analytics, owning the transformation layer from raw data to reliable models, metrics, and insights. You will turn complex People data into clean, trusted data products used across People, Finance, and Management functions.
Key responsibilities include:
- Build and own scalable, tested data models and transformations using dbt and SQL on Snowflake
- Design the data architecture and models behind People Analytics products, creating a trusted foundation for reporting and decision-making
- Build analytics products and dashboards directly in Snowflake, making reliable People data accessible across the organization
- Turn ambiguous questions from People, Finance, and Management into robust analyses and reusable data products
- Use Python to integrate internal and external data sources, work with APIs, and automate data workflows
- Leverage AI tools such as Claude to accelerate data modeling, development, and analysis
- Establish strong standards for data quality, testing, documentation, and maintainability
- Monitor and troubleshoot data pipelines and jobs, identifying root causes and improving reliability
- Use workflow automation tools such as n8n to automate processes and connect data and systems
- Partner with the wider Data Intelligence organization to align on architecture, tooling, and engineering standards
You will work hands-on with SQL, dbt, Snowflake, and Python, with significant ownership over how People data is modeled, tested, and made accessible across the organization.
FlixBus offers a hybrid work model with flexibility, travel perks (12 free Flix vouchers plus 12 discount vouchers), the ability to work from another location for up to 60 days per year, wellbeing support including confidential counseling, learning and development opportunities, and a mentoring program.
REQUIREMENTS:
- 8+ years of experience in analytics engineering, data engineering, or comparable data role, with substantial hands-on ownership of production data products
- Expert-level SQL, including complex transformations, query optimization, and working with large datasets
- Deep hands-on experience with dbt, including designing modular model structures, testing, documentation, macros, and maintaining production-grade projects
- Strong knowledge of data modeling and ELT principles, including dimensional modeling and layered data architectures
- Hands-on experience with a modern cloud data warehouse such as Snowflake, BigQuery, or Databricks, including data modeling and performance optimization
- Strong Python skills for data extraction, transformation, and integration, including working with APIs and building reusable data workflows
- Experience with Git-based development workflows and CI/CD principles for analytics code
- Strong analytical judgment: ability to take ambiguous business questions, determine what needs to be measured, and turn it into a reliable data solution
- Ability to communicate complex data and findings clearly to both technical and non-technical stakeholders
- High degree of ownership and ability to work independently from problem definition through to production
- Curiosity about AI-assisted analytics and engineering and interest in using new tools to improve how data work gets done
NICE TO HAVE:
- Hands-on experience using AI-assisted development tools such as Claude Code, coding agents, or similar tools in analytics or engineering work
- Experience building with AWS Cloud and Terraform
- Experience with workflow automation or orchestration tools such as n8n, Airflow, or similar
- Experience with data quality, observability, or job-monitoring tools such as Datadog
- Experience with forecasting, predictive analytics, or statistical modeling
- Experience working with Workday or other HR/People systems
- Experience working with People, workforce, or financial data
