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Data Analytics Engineer @ Nokia

Wrocław, Lower Silesia, PLOnsiteFull-timeJob reference 40973
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About this role

Advancing connectivity to secure a brighter world.

Nokia is a global leader in connectivity for the AI era. With expertise across fixed, mobile and transport networks, powered by the innovation of Nokia Bell Labs, we’re advancing connectivity to secure a brighter world.

Learn more about life at Nokia.

Our recruitment process

We act inclusively and respect the uniqueness of people. Our employment decisions are made regardless of race, color, national or ethnic origin, religion, gender, sexual orientation, gender identity or expression, age, marital status, disability, protected veteran status or other characteristics protected by law. We are committed to a culture of inclusion built upon our core value of respect.

If you’re interested in this role but don’t meet every listed requirement, we still encourage you to apply. Unique backgrounds, perspectives, and experiences enrich our teams, and you may be just the right candidate for this or another opportunity.

The length of the recruitment process may vary depending on the specific role's requirements. We strive to ensure a smooth and inclusive experience for all candidates. Discover more about the recruitment process at Nokia.

Our team supports Nokia's Mobile Infrastructure (MI) business segment. We manage the MI portfolio of IT tools and applications, including tool governance and coordination with corporate IT. We also develop and maintain automated MI metrics solutions, using business data to build Power BI dashboards and reports. With team members in Finland, Romania, Poland, and India, we bring a multinational perspective to MI and work across an end-to-end data analytics process, using AI tools to improve efficiency.

This is a hybrid role, with 2 days per week working from the Wrocław office.

  • Own the end-to-end development and day-to-day operation of a business-critical data platform.
  • Develop and maintain the central SQL database, including data models, calculations, consolidation logic, and integrations to ensure consistent figures across sustainability and related business use cases.
  • Build and maintain automated integrations and data pipelines across multiple enterprise data sources, including monitoring, performance optimization, troubleshooting, and failure handling.
  • Provide trusted, well-documented datasets for Power BI and other business users, with clear data lineage, definitions, calculation rules, and alignment with business data and process owners.
  • Maintain data quality controls, traceability, access management, and version management to support accurate and auditable reporting.
  • Work closely with business and technical stakeholders to understand processes, data definitions, calculation rules, and reporting requirements, translating them into reliable, maintainable, and increasingly automated solutions.
  • Continuously improve the platform, technical documentation, operational practices, automation, and data quality.
  • Minimum 3 years of SQL experience, including database development and administration, performance tuning, data processing and modeling (relational and dimensional), optimized queries, and database-level transformations and calculations.
  • Minimum 2 years of experience building and maintaining data pipelines and integrations, plus minimum 2 years of hands-on Python experience for automation, data validation, reconciliation, and operational tooling. Azure services (e.g., Azure SQL Database, Azure Data Factory, Logic Apps) are a plus; familiarity with Blob Storage and SharePoint sources is valuable.
  • Minimum 2 years of Power BI experience, with a focus on governed semantic layers, reliable datasets, and documented metrics rather than report development alone.
  • Understanding of data governance in a business context, including data definitions, ownership, access restrictions, auditability, traceability, and controlled publication of figures for reporting cycles.
  • Business understanding or experience in sustainability, product, operational data, or similar regulated reporting domains, with the ability to work with mandatory reporting requirements, investigate discrepancies across data sources, and explain how reported figures are calculated.
  • Strong analytical and structured working style, with attention to accuracy and reproducibility. Ability to work independently, take end-to-end ownership, communicate clearly with business and technical stakeholders, and continuously improve automation, documentation, and maintainability while balancing agile delivery with appropriate reporting controls.

Skills

SQLPythonPower BIAzure SQLAzure Data FactoryData PipelineData GovernanceData qualitydata lineagePerformance TuningSharePoint

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