Data Solution Data Lead Hoofddorp · hybrid

Devleaps

Hoofddorp

Hybrid

EUR 110,000 - 150,000

Full time

23 hours ago
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Job summary

Devleaps is seeking a Data Tech Lead to steer data engagements from architecture to value-driven delivery. You will own data estate architecture, translate it into a roadmap, and collaborate with CTO/CDO and client teams to ensure measurable business impact.

The role requires senior technical influence, strong stakeholder management, and a pragmatic, no-hype mindset. You will lead modernisation initiatives, govern data products, and align platform improvements with real decisions.

Qualifications

  • 6–10+ years of data or software engineering experience.
  • Track record of scoping and delivering data platforms and analytics solutions mapped to business outcomes.
  • Strong data modelling judgement: dimensional, data vault, or lakehouse layering.
  • Hands-on with SQL and Python (or Scala) and modern transformation/orchestration stack.

Responsibilities

  • Lead technical direction on data engagements and architecture.
  • Act as the trusted data voice for clients and challenge metrics.
  • Sequence platform delivery by value and business impact.
  • Drive governance as an enabler, not a paperwork burden.
  • Lead modernisation from legacy warehouses to a governed lakehouse.
  • Own the technical narrative and de-risk plans for CTO/CDO.

Skills

Data architecture leadership
SQL
Python
Scala
dbt
Airflow
Databricks
Cloud platforms
Stakeholder management
Dutch & English communication

Education

Bachelor's degree in a relevant field

Tools

dbt
Airflow
Dagster
Databricks
Snowflake

Job description

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.
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