Data Analytics Engineer
Nokia is hiring a Data Analytics Engineer. Level rates it ; you can apply on Nokia.
Level's read on this job
- Level rates this role Little AI ●○○○: aI is not part of the work.
- Level classifies it as a mid-level role.
- Level lists 568 other open roles at Nokia.
- The role was posted within the past week.
AI in this role
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.
How we rate this
Data Analytics Engineer at Nokia rates 23 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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