Services
AI and Cursor enablement for data teams, engineering maturity, and hands-on delivery — working solutions, not slide decks.
Enable data teams with AI & Cursor
Two years shaping context (prompts, repos, rules, reviews) and Cursor workflows so your data team ships faster — without accumulating unmaintainable glue code. Coaching, pair context and agent engineering, or short embedded stints, including usage policies for Cursor and other AI tools.
Data-team enablement provides your team with a full AI implementation: guidelines, risk assessment and pairing sessions.
Cursor for software teams
Accelerate regular software teams with Cursor as the development environment, including usage policies for Cursor and other AI tools. Context engineering, review loops, and workflows that keep code maintainable — whether your team builds applications, APIs, or internal tools.
Git and a steady way to ship
Help the data team move from ad-hoc scripts to a shared codebase in Git and a repeatable way to release.
Data engineering
Design and implement scalable data integration: ingestion, transformation, orchestration, and operational monitoring. Emphasis on reliable patterns, testing, and documentation so your team can own the solution.
Relevant experience: At Ellab I worked as Data Engineer on a financial data platform and financial BI with Microsoft Fabric, Azure Data Factory, Microsoft SQL, Jira, and Cursor / AI-assisted workflows.
Data warehousing
Warehouse and mart design: dimensional modelling, slowly changing dimensions, data quality checks, and performance tuning for heavy read workloads.
Relevant experience: At Ellab I worked as Data Engineer on a financial data platform and financial BI with Microsoft Fabric, Azure Data Factory, Microsoft SQL, Jira, and Cursor / AI-assisted workflows.
Hands-On Development & Consulting
Embedded technical support, implementation, and platform build-out — from shaping the approach to writing the code and shipping the solution. Engagements can include assessments, pair delivery with your team, or interim hands-on capacity alongside your roadmap.
A typical engagement lasts 3–6 months and combines remote and on-site work.
Questions about AI and Cursor enablement
How do you help a data team use AI and Cursor effectively?
I work with your data engineers through coaching, pair context and agent engineering, or a short embedded stint. The work covers context — prompts, repositories, rules, and reviews — plus Cursor workflows and usage policies for Cursor and other AI tools, so the team ships faster with AI-assisted workflows that stay maintainable. Working solutions, not slide decks.
What is AI enablement coaching for data engineers?
Hands-on coaching that helps your data engineers work effectively with AI tools and Cursor in their day-to-day delivery. It draws on two years of context engineering and Cursor workflows, and on 20+ years of data platforms in regulated and finance environments. The aim is shorter lead times from idea to running code, with changes that stay understandable, testable, and portable when the model is no longer in the loop.
What is pair context and agent engineering?
It means working alongside your engineers to shape the context an AI agent works from — prompts, repository and product context, rules, tool choice, and review loops — inside environments like Cursor. Rather than handing over a document, we build that context together in your real codebase, using small, reviewable steps and explicit assumptions.
How can Cursor help a data team ship faster without messy glue code?
By shaping the context Cursor works from — prompts, repos, rules, and reviews — and pairing that with review loops and small, reviewable steps. The goal is faster delivery without accumulating unmaintainable glue code, and with honesty about where automation helps and where human judgment is non-negotiable.
What does a short embedded AI enablement stint look like?
I join your team for a limited period and work inside your roadmap: from shaping the approach to writing the code and shipping the solution, alongside your engineers, including Cursor workflows and usage policies for Cursor and other AI tools. Engagements can include an assessment, pair delivery with your team, or interim hands-on capacity.
How do you set usage policies for Cursor and AI tools on a team?
Usage policies for Cursor and other AI tools are included in both data-team enablement and Cursor for software teams. They're set together with your team as part of adopting AI-assisted delivery, using the same standards I learned in regulated and data-heavy settings: explicit assumptions, reviewable changes, and clear lines on where human judgment is required.
How do you introduce Git and a steady way to ship on a data team?
By helping the team move from ad-hoc scripts to a shared codebase in Git and a calm, repeatable way to release. It raises the team's engineering habits: one shared codebase and a repeatable release.
Do you also work with regular software teams?
Yes. Cursor for software teams accelerates teams building applications, APIs, or internal tools with Cursor as the development environment — context engineering, review loops, usage policies, and workflows that keep code maintainable.
Can you also do hands-on data engineering and warehousing?
Yes, when you need it. I design and build data integration on Azure, SQL Server, and Microsoft Fabric — ingestion, transformation, orchestration, and monitoring — and warehouse and mart design with dimensional modelling, slowly changing dimensions, data quality checks, and performance tuning. AI and Cursor enablement remains the main offer.
Where do you work?
I work with data teams throughout Denmark, both remotely and on-site, in Danish and English.
How do I get in touch?
Email [email protected], call +45 23 61 21 91, or message me on LinkedIn. See contact.
Idea, no upfront budget?
If you have a strong idea but no money for a traditional build, we can still talk: I can help deliver the technical solution on a profit-sharing (or revenue-share) basis when the fit is right — clear scope, shared risk, and terms we both sign up to. Every case is different; reach out with what you are building and we can explore whether it makes sense.