Solution Data Lead

Engineering is human. So are you. A data platform is a means to a better decision, not the point.

At Devleaps, we build data platforms so finance, ops and product decide from the same numbers — and we hand them back to a team that can run them. We're looking for a Data Tech Lead who sequences that work around business value and can defend every line of the roadmap.

WHAT YOU'LL DO

• Lead technical direction on data engagements: own the architecture of the data estate and translate it into a roadmap with sequencing, cost and ownership attached.
• Serve as the trusted data voice for clients: challenge which metrics actually matter, and say plainly when the data cannot answer the question being asked.
• Sequence the platform around value: deliver the domain or use case that unblocks a real decision first, and make the platform the thing that makes the next five cheaper.
• Make governance an enabler, not paperwork: ownership, stewardship and contracts framed as what makes data usable and safe, rather than a compliance tax.
• Drive modernisation at scale: lead migrations from legacy warehouses and fragmented estates towards a governed lakehouse, sequenced by business impact rather than technical tidiness.
• Own the technical narrative: facilitate reviews and workshops that turn 'we need to be data-driven' into a scoped, costed, de-risked plan for a CTO or CDO.
• Remove what slows teams down: find the systemic bottleneck — unclear ownership, access friction, quality nobody is accountable for — and fix the actual constraint.

YOU ARE

• A seasoned engineer who has led: you have made architectural calls and owned outcomes, and you know the difference between a good model and a model that ships value this quarter.
• A consultant at heart: you ask before you prescribe, and you are comfortable telling a stakeholder their favourite metric is not measurable yet.
• Comfortable with ambiguity and politics: competing stakeholder interests, data ownership disputes, and legacy constraints do not slow you down.
• Outcome minded: you measure success by decisions improved, not dashboards delivered.
• Human, practical, and allergic to hype decks.

YOU'LL BRING

• 6–10+ years of data or software engineering experience, with a few years in a lead, principal or data architect capacity.
• A track record of scoping and delivering data platforms and analytics solutions that mapped to a named business outcome.
• Strong data modelling judgement: dimensional (Kimball), data vault or lakehouse layering, and the ability to explain the trade-offs in business terms.
• Strong SQL plus solid Python (or Scala), and hands-on experience with a modern transformation and orchestration stack (dbt, Airflow, Dagster, Databricks).
• Hands-on experience with at least one major cloud data platform — Azure (Fabric, Synapse), AWS, or GCP (BigQuery). We see all three in data engagements.
• Working knowledge of streaming and CDC ingestion, and a clear view of when real-time earns its cost.
• Practical grasp of data governance and data products: ownership, contracts, cataloguing, access control, and GDPR-relevant handling of personal data.
• A clear view of where data investment genuinely pays off, based on real delivery rather than vendor claims.
• Proven consultancy skills: stakeholder management, difficult conversations, and clear recommendations under pressure.
• Comfortable operating from junior engineer to VP of Engineering, and credible with a CDO or finance stakeholder.
• Fluent Dutch, professional English.