Data Analyst / Analytics Engineer

84185
  • Market related
  • Europe

Data Analyst / Analytics Engineer

Location: Solna, Stockholm, Sweden
Start Date: 1st October 2026
End Date: 31st March 2027
Work Style: Monday - Friday / Hybrid, 40 Hours Weekly

Role Objective

  • Support the Power Forecasts product team in producing local-grid and regional-grid forecasts for housing, transport electrification, industry, and commercial premises.
  • Maintain and improve a data-driven, automated forecasting workflow centred on Python scripts.
  • Produce reliable forecasts and insights for network dimensioning, network-development planning, investment decisions, and customer dialogue.
  • Enhance the quality, efficiency, and analytical value of forecasting, data-modelling, and reporting processes.

Key Responsibilities

  • Automate forecasting activities previously completed manually using Python within a Databricks environment.
  • Analyse customer and time-series data to develop improved forecasting methodologies.
  • Build new Power BI reports and enhance existing reports through data modelling, calculations, and additional functionality.
  • Update power forecasts for specific geographical areas and generate quantitative and qualitative insights.
  • Assess data availability, combine information from multiple sources, and ensure data quality and reliability.
  • Communicate analytical findings clearly to internal and external stakeholders.

Tasks

  • Develop clear and efficient Python code to automate forecast preparation and processing.
  • Conduct both defined analyses and exploratory investigations into customer and time-series data.
  • Collaborate with colleagues from other disciplines to assess potential changes to forecasting methodology.
  • Develop Power BI data models, calculations, visualisations, and report functionality.
  • Gather, validate, process, and quality-assure input data used in power forecasts.
  • Liaise with municipalities and local-grid customers when updating forecasts for specific areas.
  • Prepare and present forecast results, insights, and supporting materials to relevant stakeholders.
  • Contribute to the continuous development of automated and data-driven ways of working within the product team.

Deliverables

  • Automated and maintainable forecasting workflows within Databricks.
  • Updated local-grid and regional-grid power forecasts.
  • Customer-data and time-series analyses supporting methodology development.
  • Accurate and usable Power BI reports, data models, and calculations.
  • Quality-assured datasets, analytical insights, and stakeholder presentation materials.

Decision Authority / Responsibility

  • Own assigned analysis, automation, reporting, and forecast-update activities through to completion.
  • Recommend improvements to forecasting methodologies, data models, and automated workflows based on evidence and analysis.
  • Identify and escalate material data-quality, reliability, and methodological risks.
  • Ensure analytical results and reporting outputs are clear, reliable, and suitable for stakeholder decision-making.

Requirements

  • Several years of experience analysing large datasets, particularly customer data and time series, including data manipulation, modelling, and presentation of results to stakeholders.
  • Several years of experience developing efficient, understandable code using Python or a comparable programming language.
  • Professional experience in the electricity-network sector or other relevant energy-industry experience.
  • Professional experience with data-visualisation tools such as Power BI.
  • Strong analytical ability and advanced problem-solving skills.
  • Able to communicate complex findings and messages clearly to different stakeholders.
  • Relevant academic degree, such as an MSc in Engineering in Applied Physics, Energy Systems, Electrical Power Engineering, or another relevant technical discipline.
  • Previous experience in insight generation and/or forecasting is advantageous.
  • Experience working in an Agile Scrum team or equivalent environment is advantageous.
  • Experience with artificial intelligence and machine learning is advantageous.
  • Experience with SQL or an equivalent query language is advantageous.

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