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Enpal is seeking a Senior Analytics Engineer to join their team and drive data-driven decision-making across ERP, Supply Chain Management, and Logistics functions.
In this role, you will own analytics projects end-to-end, from initial requirements gathering through data modeling and delivery. You'll partner closely with business stakeholders to understand their objectives and translate complex business questions into clear, reliable, and actionable data solutions. The position combines stakeholder management, business analysis, hands-on analytics work, and modern data engineering, with access to advanced Agentic AI toolkits to help you deliver high-quality data products efficiently.
Key responsibilities include:
- Partnering with business stakeholders across ERP, SCM, and Logistics to understand objectives and analytical needs
- Translating business requirements into scalable data models and analytical solutions
- Taking end-to-end ownership of analytics projects, including scoping, prioritization, delivery, and stakeholder communication
- Building and maintaining reliable data models and transformations using SQL and dbt
- Designing scalable, business-ready data models that provide a trusted foundation for decision-making
- Ensuring data quality, consistency, and transparency across analytical products
- Owning new data integrations in the ERP and SCM domain, working closely with data engineers and business teams
- Identifying opportunities to simplify or automate recurring reporting and operational workflows
- Leveraging Agentic AI and LLM-based tools to deliver high-quality data products
- Communicating progress, risks, dependencies, and recommendations to both technical and non-technical audiences
- Contributing to analytics standards, documentation, and knowledge sharing across the team
The company values curiosity, sound analytical judgment, and a willingness to learn. You should enjoy understanding complex problems, collaborating with different teams, and building solutions that create measurable business value.
Requirements:
- 5+ years of experience in business intelligence, analytics, analytics engineering, data engineering, or comparable role
- Strong understanding of data modeling, data quality, and analytical best practices
- Practical experience with data engineering concepts, including 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 their 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 approach to work
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 other operationally complex environments
- Experience supporting senior stakeholders with decision-ready insights
