Data Analyst

We are looking for a Data Analyst / Analytics Engineer to join the Power Forecasting product team within the organization responsible for electricity grid forecasting.The team develops power forecasts for both local and regional electricity grids. These forecasts estimate future additional power demand across areas such as residential development, transport electrification, industry, and commercial facilities.The forecasts play an important role in grid planning, network development, investments and reinvestments, and customer engagement.The team has transitioned from traditionally Excel-based processes toward a data-driven and automated forecasting environment, with Python and Databricks playing a central role.Key ResponsibilitiesForecasting AutomationAutomate existing manual forecasting processes using Python.Develop and maintain solutions within a Databricks environment.Improve the efficiency, scalability, and reliability of forecasting workflows.Data Analysis & Methodology DevelopmentAnalyze customer data and time-series data to identify trends and opportunities for improving forecasting methodologies.Perform both structured and exploratory data analysis.Collaborate with colleagues and subject-matter experts across different disciplines.Translate analytical findings into actionable insights.Power BI & ReportingDevelop new and enhance existing Power BI reports and dashboards.Perform data modeling and implement calculations.Improve reporting functionality, usability, and performance.Present analytical results clearly to business stakeholders.Power Forecast UpdatesUpdate power forecasts for specific geographical areas.Collect, validate, and process input data.Collaborate with municipalities and local-grid customers when required.Generate quantitative and qualitative insights from forecast results.Prepare presentations and supporting materials for stakeholders.Data Quality & AnalysisIdentify and assess the availability of relevant data.Collect and consolidate data from multiple sources.Perform data validation and quality assurance.Ensure that analytical outputs are accurate, reliable, and fit for purpose.Required Qualifications & ExperienceThe successful candidate should have:Several years of experience in data analysis, particularly working with Big Data, customer data, and time-series data.Experience with data manipulation, data modeling, and reporting.Strong programming skills in Python or a comparable programming language.Professional experience with Power BI or similar data visualization tools.Previous experience within the energy sector, electricity grid industry, or a closely related field.Strong analytical and problem-solving capabilities.Excellent communication skills and the ability to communicate complex analytical findings to stakeholders.Preferred QualificationsThe following experience would be considered an advantage:Experience in forecasting and/or business insight development.Experience working in Agile/SCRUM environments.Knowledge or practical experience in AI/ML.Experience with SQL or equivalent data-querying technologies.EducationA relevant academic degree is required, preferably in a technical or engineering discipline, such as:Engineering PhysicsEnergy SystemsElectrical Power EngineeringData/Analytics-related disciplinesOther relevant technical or engineering fieldsAssignment Details:Client: VattenfallRole: Data Analyst / Analytics EngineerFocus Area: Power ForecastingLocation: Solna, Stockholm, SwedenWork Model: HybridStart Date: 1 October 2026End Date: 31 March 2027Duration: 6 monthsWorking Hours: Approx. 40 hours/weekExperience: Mid-levelLanguages: Swedish & EnglishTravel: No Candidate ProfileWe are looking for a technically strong and analytically minded professional who can combine data analysis, Python development, visualization, and domain knowledge to support power forecasting.The ideal candidate is comfortable working with large and complex datasets, can independently investigate analytical problems, and is able to communicate insights effectively to both technical and non-technical stakeholders.