Data & Analytics Engineer

As our Data & Analytics Engineer, you will own data at Silverfin and be the face of data in the company. You will be the person teams turn to for data they can trust, and the person who asks whether our current setup is the best one for where we are going. Our Data team has a growing mandate in the business, and data sits at the heart of it. This role moves data from a support function to a strategic one.

You will report directly to the VP Finance and work alongside our external data consultant. As our internal data specialist, you will take the initiative, build data products that teams trust, and shape the long-term data roadmap.

Key Impact Areas:

• Data Strategy & Ownership: Own our data landscape end to end, from sources and pipelines to models and dashboards, and shape a long-term data roadmap that serves every department.

• Data Governance: Put clear ownership, definitions, quality standards and access rules in place, so the whole business works from one trusted version of the truth.

• Data Platform & Engineering: Build and run reliable, scalable pipelines and data models on our cloud stack, and propose improvements to our architecture and tooling.

• Business Partnership & Insight: Work with teams across the company to understand their needs and turn them into data products, including Looker dashboards people actually use.

• AI & Innovation: Follow what is happening in data and AI, and bring the developments that matter into how Silverfin works with data.

Data Strategy & Leadership:

• Define and drive Silverfin's data roadmap together with the VP Finance, aligned with company priorities and the needs of every department.

• Critically assess our current data setup, tools and processes, and propose improvements, simplifications or alternatives.

• Act as the go-to person and ambassador for data across Silverfin, represent data in cross-functional discussions and grow data literacy in the business.

• Own delivery of the internal data backlog (pipelines, data models, dashboards, data quality checks)

Data Engineering & Platform:

• Design, build and maintain data pipelines and integrations from our source systems into BigQuery, using Cloud Functions, fivetran and Airbyte, with GitLab for version control and deployment.

• Develop and maintain robust, well-documented data models that support scalable and accurate reporting.

• Monitor the health, performance and cost of the data platform, and resolve issues before they reach the business.

• Lead the move away from Metabase, consolidating reporting into another solution without loss of data or insight for business users.

Data Governance & Quality:

• Set up and run a data governance framework covering data ownership, KPI definitions, data quality checks and access management, in line with Visma Group standards.

• Create and maintain a data catalogue and clear documentation of sources, metrics and models.

• Make sure data is handled in line with GDPR and our information security policies.

Business Partnership & Reporting:

• Talk to teams across the business to understand their questions and needs, and translate them into data solutions.

• Build and maintain dashboards and reports in Looker, and enable teams to answer their own questions.

• Work with our external data consultant to agree priorities and divide delivery.

AI & Innovation:

• Keep up with developments in data engineering, analytics and AI, and translate them into concrete opportunities for Silverfin.

• Work with our data consultant on building AI agents for teams across Silverfin and making our data ready for agentic ways of working.

• Explore how AI can make our data more accessible, for example through self-service analytics and automation.

• The business sees you as the face of data at Silverfin and comes to you proactively with questions and ideas.

• Metabase is retired and business users can continue their work, without losing data or insight along the way.

• A data governance framework is in place: every core KPI has one agreed definition, data has clear owners and quality issues are caught early.

• A long-term, cross-department data vision and roadmap is agreed and being delivered.

• Our data setup has been critically reviewed, with clear, well-argued recommendations on what to keep, change or stop.

• You bring relevant data and AI developments to the table and turn the most promising ones into working solutions.

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Business Engineering or a related field, or equivalent experience.

• At least 5 years of experience in data engineering, analytics engineering or BI, including end-to-end ownership of a data platform or data domain.

• Hands-on experience building and maintaining data pipelines and data models in a cloud data warehouse, preferably BigQuery on Google Cloud.

• Proven experience setting up or improving data governance, and in shaping a data roadmap together with business stakeholders.

• Experience in a SaaS environment is strongly preferred.

Must-haves:

• Advanced SQL.

• Hands-on experience with a cloud data warehouse (e.g. BigQuery, Snowflake or Redshift).

• Strong knowledge of data modelling, data warehousing and ELT/ETL processes.

• Experience with at least one data visualisation tool (e.g. Looker, Looker Studio, Power BI or Tableau).

General skills:

• Good understanding of data governance, data quality and data security principles, including GDPR.

• Hands-on experience using AI in your own data work (e.g. code generation, self-service analytics) and ideas on how to apply it further.

• Strategic thinking: able to see the bigger picture and translate it into a pragmatic roadmap.

• Excellent communication skills in English, with the ability to explain technical topics to non-technical colleagues. Dutch and/or French is a plus.

Nice-to-haves:

• Python.

• Experience with Google Cloud, including BigQuery and Cloud Functions.

• Knowledge of Looker and LookML.

• Experience with data ingestion tools such as Fivetran or Airbyte.

• Version control and CI/CD, ideally in GitLab.

• Approachable and collaborative: you enjoy talking to people across the business and building relationships.

• Lots of drive and a strong sense of ownership: you take the initiative instead of waiting to be asked.

• Critical and curious: you ask the hard questions, including whether the way we do things today is the best way.

• A strategic mindset combined with a hands-on attitude: comfortable both shaping the vision and building the solution.

• Confident in representing data and in challenging stakeholders constructively.

• Resilient and adaptable in a fast-paced, growing environment.