Data Engineer
Data/Analytics Engineer building and maintaining Smartvatten's cloud data platform: ingesting data from sources like Salesforce, NetSuite and MongoDB into Google Cloud/BigQuery, modeling it with SQL/Dataform, and serving Qlik reporting and AI use cases. Onsite role in Kokkola or Pori, Finland.
- Compensation
- Not disclosed
- Location
- Kokkola, Finland
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- BSc/B.Eng. completed or ongoing in Computer Science, Data/Software Engineering or related field, or equivalent demonstrable skills
- Working knowledge of SQL
- Basic programming skills, preferably Python
- Eagerness to learn cloud data technologies
- Attention to detail
- Good communication skills in English
- Readiness to work with AI tools — experience or genuine willingness to learn
Nice to have
- Prior experience with Google Cloud Platform, especially BigQuery
- SQL-based data modeling, scheduled ingestion pipelines, version-controlled transformations (Dataform, Git)
- Data ingestion / ETL pipelines (e.g. Apache Beam / Dataflow), including reading from MongoDB / NoSQL sources
- Infrastructure as code (Terraform)
- Qlik (Qlik Cloud / Qlik Sense) or other BI / data visualization tools
Full description
Smartvatten is Europe's leading SaaS platform for data-driven water management, designed for both real estate portfolios and water utilities. Through digital monitoring, analysis and data-driven insights, Smartvatten helps its customers detect deviations early, optimise water use and make better decisions. Today, Smartvatten monitors more than 40,000 buildings, over 200,000 apartments and more than 40 water networks, contributing to more efficient operations, reduced risk and more sustainable water use.
We are now looking for a
Data Engineer to join our team in Kokkola or Pori
About the role:
As a Data / Analytics Engineer you help build and maintain Smartvatten's cloud data platform. You bring data from various source systems into our Google Cloud / BigQuery data warehouse, model it into reliable, reusable datasets, and serve it to reporting (Qlik) and other consumers. We develop with AI as an everyday tool rather than a side project, and the warehouse you build is also the foundation the company's AI and analytics use cases are built on.
Key responsibilities:
- Building data pipelines: ingesting data from source systems (e.g. Salesforce, NetSuite, MongoDB-based systems and SaaS APIs) into the BigQuery data warehouse.
- Data modeling & transformation: developing SQL transformations in Dataform following our layered (bronze - silver - gold - reporting) medallion architecture.
- Reporting datasets: building and maintaining the serve-layer tables and views consumed by Qlik dashboards and other reporting.
- Data quality & documentation: writing tests/assertions, validating results, and documenting datasets and KPI definitions.
- Collaboration: Work with the technology team and stakeholders to turn reporting and KPI needs into data solutions.
- AI in practice: using AI-assisted development in your daily work and building the datasets that make AI and analytics use cases possible — including a governed dataset, free of personal data, that AI tools can query safely.
Skills and competences needed in this role:
Required / core
- BSc/B.Eng. completed or ongoing in Computer Science, Data/Software Engineering or a related field — or equivalent demonstrable skills.
- Working knowledge of SQL.
- Basic programming skills, preferably Python.
- Eagerness to learn cloud data technologies, attention to detail, and good communication skills in English.
- Readiness to work with AI tools — either existing experience or a genuine willingness to learn. You do not need to have built AI systems; you do need to be interested in where they can be applied.