Senior Analytics Engineer (f/m/x) - Enpal Energy

• Model clean, well-documented datasets in dbt (staging → marts), including tests, ownership, and clear metric definitions.
• Lead the development and evolution of our semantic layer - defining governed business metrics, dimensions, and data contracts that serve as the single source of truth to downstream AI tools.
• Structure dbt models, metric definitions, and documentation so they are machine-readable and ready to serve as reliable context for AI-powered analytics tools.
• Diagnose messy or ambiguous source data, reconcile inconsistencies, and align stakeholders on a single source of truth.
• Optimize Snowflake query performance, data freshness, and quality through testing and monitoring.
• Partner with BI and business teams to design certified datasets, dashboards, and self-service standards.
• Develop reporting end-to-end — from understanding business needs to delivering actionable, intuitive data products.
• Maintain and evolve central data pipelines, dbt models, and Tableau integrations within a modern stack (Python, AWS/Azure/GCP, Git).
• Act as a technical mentor for the team, helping others adopt best practices in analytics engineering and embrace new tooling - including AI-assisted development.

What you'll bring

• 5+ years of experience as an Analytics Engineer, BI Developer, or Data Engineer.
• Proven record of turning complex, large-scale data into actionable insights and governed metrics used across BI.
• Expert in SQL and data modeling (star schemas, dimensions/facts, semantic layer design).
• Hands-on experience building production-grade dbt projects with testing, documentation, and version control workflows.
• Strong proficiency in Python for analytics tasks (data checks, automation, utilities).
• Strong stakeholder management and communication skills — able to translate business logic into durable, scalable data models.
• Familiarity with ELT concepts, CI/CD for analytics code, data cataloging, and basic cost/performance tuning.
• Self-starter with a hands-on, problem-solving mindset, comfortable balancing autonomy and collaboration in a fast-moving environment.
• Genuine curiosity about how AI is reshaping the analytics engineering role - comfortable experimenting with AI-assisted development tools and motivated to help the team adopt them thoughtfully.
• Experience with or strong interest in semantic layer tooling (dbt MetricFlow, Snowflake semantic views, or similar) and how it enables both self-service analytics and AI-ready data products.

Are you interested even if you don't meet all the requirements? Apply anyway! We look forward to discovering your potential—regardless of whether your experience meets every single requirement. ☀️