Analytics Engineer (m/f/d)

Posted Yesterday
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Berlin, DEU
In-Office
Senior level
Greentech • Energy • Solar • Renewable Energy
The Role
Own end-to-end analytics projects from requirements through delivery. Build scalable data models and transformations using SQL and dbt, integrate ERP and supply-chain data, ensure data quality, automate reporting workflows, and communicate insights to technical and business stakeholders. The role also involves leveraging Agentic AI and LLM tools to develop efficient, business-ready data products.
Summary Generated by Built In

About the role

We are looking for a (Senior) Analytics Engineer to join our team. In this role, you will work closely with stakeholders across ERP, Supply Chain Management, Logistics to turn complex business questions into clear, reliable and actionable data solutions.

You will take ownership of analytics projects from initial requirements through data modelling and delivery. The role combines stakeholder management, business analysis, hands-on analytics and modern data engineering, with an advanced Agentic AI toolkit at hand to help you deliver high-quality data products efficiently.

Your responsibilities

  • Partner with business stakeholders to understand their objectives, processes and analytical needs.

  • Translate business requirements into scalable data models and analytical solutions.

  • Take end-to-end ownership of analytics projects, including scoping, prioritisation, delivery and stakeholder communication.

  • Build and maintain reliable data models and transformations using SQL and dbt.

  • Design and develop scalable, business-ready data models that provide a trusted foundation for decision-making.

  • Ensure data quality, consistency and transparency across analytical products.

  • Own new data integrations in the ERP and SCM domain, working closely with data engineers and business teams from source onboarding through production.

  • Identify opportunities to simplify or automate recurring reporting and operational workflows.

  • Leverage Agentic AI and LLM-based tools to deliver high-quality data products efficiently.

  • Communicate progress, risks, dependencies and recommendations clearly to both technical and non-technical audiences.

  • Contribute to analytics standards, documentation and knowledge sharing across the team.

What you bring

  • 5+ years of experience in business intelligence, analytics, analytics engineering, data engineering or a comparable role.

  • A good understanding of data modelling, data quality and analytical best practices.

  • Practical experience with data engineering concepts, including data pipelines, transformations, SQL/dbt and cloud data platforms.

  • Experience working with modern data warehouses such as Snowflake, BigQuery, Redshift or similar.

  • Knowledge of or hands-on experience with ERP systems such as Microsoft Dynamics 365 or SAP, including their business processes and underlying data.

  • The ability to understand business processes and translate them into effective data solutions.

  • Strong stakeholder-management and communication skills.

  • A structured, proactive and ownership-driven way of working.

Nice to have

  • Experience or strong interest in Agentic AI, LLM-based applications and AI-powered workflow automation.

  • Hands-on experience developing AI agents, prototypes or automated analytical workflows.

  • Experience with Python and APIs.

  • Familiarity with orchestration, version control and software-development practices.

  • Experience in ERP, Supply Chain Management, Logistics, energy or another operationally complex environment.

  • Experience supporting senior stakeholders with decision-ready insights.

What we value

You do not need to be an expert in every technology from day one. We value curiosity, sound analytical judgement and a willingness to learn. You should enjoy understanding complex problems, collaborating with different teams and building solutions that create measurable business value.

Skills Required

  • 5+ years of experience in business intelligence, analytics, analytics engineering, data engineering, or a comparable role
  • Understanding of data modeling, data quality, and analytical best practices
  • Practical experience with data engineering concepts, data pipelines, transformations, SQL, dbt, and cloud data platforms
  • Experience with modern data warehouses such as Snowflake, BigQuery, Redshift, or similar
  • Knowledge of or hands-on experience with ERP systems such as Microsoft Dynamics 365 or SAP, including business processes and underlying data
  • Ability to understand business processes and translate them into effective data solutions
  • Strong stakeholder-management and communication skills
  • Structured, proactive, and ownership-driven working style
  • Experience or strong interest in Agentic AI, LLM-based applications, and AI-powered workflow automation
  • Hands-on experience developing AI agents, prototypes, or automated analytical workflows
  • Experience with Python and APIs
  • Familiarity with orchestration, version control, and software-development practices
  • Experience in ERP, supply chain management, logistics, energy, or another operationally complex environment
  • Experience supporting senior stakeholders with decision-ready insights
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The Company
4,994 Employees
Year Founded: 2017

What We Do

Enpal GmbH is a German greentech company providing all‑in‑one residential decarbonisation solutions: rooftop solar PV systems, battery storage, EV wallboxes, heat pumps and an intelligent energy manager (Enpal.One). Customers can rent or buy systems with integrated installation, financing, maintenance and energy‑trading features. Enpal aggregates distributed home resources into virtual power‑plant services to optimise energy flows and lower household energy costs.

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