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

Meyandy LLC; Berlin; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

Enpal Energy, the electricity division of Enpal, is hiring a Senior Analytics Engineer in Berlin to build robust data platforms. You will model datasets in dbt, lead semantic layer development, and ensure trusted metrics for AI-powered analytics across the organization.

Ideal candidates have 3+ years in analytics engineering, strong SQL, Python, and experience with dbt, Snowflake, and Tableau. Join a fast-moving, tech-forward team shaping the energy transition.

Qualifikationen

• 3+ 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.

Aufgaben

• 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.

Kenntnisse

SQL proficiency

Data modeling

Python

Stakeholder management

ELT concepts

CI/CD for analytics

Data cataloging

Self-starter mindset

AI-resilience curiosity

Semantic layer tooling

Tools

dbt

Snowflake

Tableau

Git

Cloud (AWS/Azure/GCP)

Jobbeschreibung

Senior Analytics Engineer (f/m/x) - Enpal Energy — Enpal, Berlin.

Our goal is to have a solar system on every roof, a storage unit in every house, and an electric car in every garage. Enpal makes this possible with an integrated total solution for decentralized energy—from solar systems and battery storage to wall boxes, smart meters, and heat pumps. At the heart of it all is our AI-powered platform Enpal.One+, which intelligently connects thousands of systems and efficiently optimises electricity procurement and feed-in on the energy market. Enpal Energy is Enpal’s electricity division, making clean energy accessible to every household—from Germany’s most affordable electricity rates to smart energy solutions that optimally integrate generation, storage, and consumption. With ambitious growth targets and a rapidly expanding customer base, we are building a team that is actively shaping the German energy market. In doing so, we combine startup agility with the scale of a market leader—across all areas, from operations and technology to finance, customer support, and product development.

What you’ll do

• 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.

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

What you’ll bring

• 3+ 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.

What we offer

Work at Germany's first green unicorn - Play an active role in shaping the solar energy transition. The sun shines all over the world - At Enpal, you'll work with a highly motivated, diverse team o…

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