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Salary: EUR 85,000 - 110,000 / annual
Lead Insify's Data & Analytics team of 3–4 engineers across the full data stack: ingestion, warehouse, models, metric layer, and reporting. This is a hands-on manager role where you own both the team and the technical direction. You'll work with four distinct internal stakeholders—Growth (hourly/daily signals, approximate accuracy), Carrier Reporting (calendar-locked, audit-proof reconciliation), Corporate Finance (reconciliation and auditability), and Actuarial (depth and lineage)—each with different needs and failure modes. You'll arbitrate priorities, make trade-off decisions, and ensure the platform scales as the company enters new countries and products.
Key responsibilities include:
- Leading the team end-to-end: hiring, performance management, technical mentorship, and growth
- Running discovery with internal stakeholders to understand data needs and shape platform priorities
- Owning the trade-off decisions between competing demands; saying no when necessary
- Driving platform scalability through configuration, reusable models, and automation (e.g., carrier reporting, cash reconciliation)
- Bringing engineering excellence: data contracts, CI testing, production safety, and change management
- Staying hands-on: reviewing models before they ship, reading the warehouse, and maintaining technical credibility with your team
- Challenging ideas and encouraging the same from others
The role is deliberately unsplit between data engineering and analytics because the hard problems sit at the handover. You'll need to reason about systems, prioritization, and people—not just tools.
Tech stack: Databricks with Unity Catalog, dbt with SQL-based transformation, AWS. Stack knowledge is not a hard requirement; reasoning about data systems matters more.
Requirements:
- Proven experience managing or leading a data team (hiring, feedback, people development). Must be real and substantive, and you must want to do more of it.
- Depth on one side of the data stack (engineering or analytics) and working fluency on the other. You still ship, review team work, and your team trusts your technical judgment.
- Track record of shaping what gets built, not just how. You've translated business problems into data priorities, cut scope, and can articulate the decisions that followed.
- Ownership and impact instinct: you go beyond team boundaries to drive results when needed.
- Hands-on experience with AI tools in daily work; you can articulate where they help and where they hurt. You trial new tools first and bring the ones that stick to your team.
Nice to have:
- Experience with reconciliation-critical reporting (bordereaux, revenue, cash, ledger)
- B2B product experience, especially in insurance or fintech
- Multi-country product experience
- Databricks, dbt, or event tracking (Snowplow) experience
