As Data Lead, you play a defining role in building and leading LYNX’s end-to-end data domain — evolving the organisation from a fragmented, application-centric setup into a scalable, platform-driven data ecosystem that puts trustworthy data in the hands of everyone who needs it.
We are looking for a Data Lead to own our data domain end to end — spanning Data Platform, Analytics, and Data Science — and to make data-driven decision-making the default across LYNX. This is a hands-on leadership role with a strong transformation mandate.
You join at a pivotal moment. The data platform has been selected and its base configuration and set-up are complete, and recruitment for the team is already underway. Your focus is to build on that foundation — maturing the platform into a genuine self-service ecosystem, embedding standards and adoption across the business, and establishing the foundations for AI and ML along the way.
You will shape the team as it comes together — onboarding and developing the Data Platform Engineer and Data Analytics Engineer joining the team, leading and growing the Data Science capability, and providing functional leadership to the analysts embedded across our squads. Your work will directly influence how LYNX makes decisions, meets its regulatory obligations, and turns its data into commercial value. You will report to the Head of Engineering, though much of your influence will be lateral — aligning stakeholders across the organisation and creating consistency without relying solely on direct reporting lines.
What you’ll do
- Own the Data Domain End-to-End: Lead LYNX’s data domain across Data Platform, Analytics, and Data Science, owning the strategy, architecture, governance, standards, and roadmap.
- Solve Structurally, Not Ad-Hoc: Look past individual stakeholder requests to spot recurring problems and antipatterns, design structural solutions within the data domain, and influence other departments to adopt best practices — rather than firefighting one-off issues.
- Mature the Platform & Enable Self-Service: Build on the selected, base-configured platform — evolving the data warehouse, catalog, managed ingestion, and semantic/metrics layer, along with the access models and tooling — so teams across the business can find, understand, and act on data independently, with governance layered in at the core rather than bolted on later.
- Raise Data Maturity Across the Company: Improve how data is captured, owned, and used at the source, not just in the warehouse — redesigning processes together with teams where they produce unreliable data or unworkable reporting. Build data literacy, ownership, and the reflex to consult data before committing to a direction, so departments treat good data as part of their job rather than the data team’s problem.
- Define the Future of Analytics: Shape a clear vision for how AI will change analytics at LYNX — from AI-assisted data access and natural-language querying to ML-driven insights — and prepare the platform, semantic layer, and team so that vision can be built reliably on well-described, well-governed data.
- Partner with Leadership on High-Impact Questions: Work with leadership on the questions that move the business — pricing, retention, growth efficiency, capacity planning — and deliver analyses that visibly change decisions, building the function’s credibility through those wins.
- Build & Develop the Team: Complete and onboard the team already being recruited — including a Data Platform Engineer and a Data Analytics Engineer — and coach the wider data community toward high-impact work.
- Lead the Data Science Capability: Lead and develop Data Science, initially as a centralised team and over time toward a hybrid model where Data Scientists partner closely with squads while remaining part of the data organisation.
- Provide Functional Leadership to Analysts: Give functional leadership across the analyst community — defining standards, shared practices, and priorities together with the Engineering Managers.
- Support Regulatory Reporting: Support the evolution of financial and regulatory reporting — a specialised but business-critical part of the domain — by ensuring the underlying data platform, governance, and data quality meet the standards expected by regulators.
- Set Governance Standards: Establish clear ownership, lineage, quality, and privacy standards across all data domains — pragmatic accountability that enables rather than bureaucracy that slows, making compliance a byproduct of good practice rather than a separate effort.
- Lay the AI/ML Foundations: Prepare the platform and semantic layer so AI-assisted access and ML use cases can be built reliably on well-described, well-governed data.
Who you are
You are an experienced data leader who combines a deep technical understanding with the ability to build teams, set direction, and bring an organisation along. You are as comfortable shaping architecture as you are coaching people and making the case for investment to senior stakeholders.
- You have significant experience building and leading data teams or a data domain, ideally through a period of transformation
- You have strong knowledge of modern data platform architecture — warehousing, ingestion, cataloging, dbt-based modelling, and semantic layers
- You understand Data Platform, Analytics, and Data Science well enough to set direction across all three
- You have hands-on experience with market-standard data tooling and a pragmatic build-vs-buy mindset
- You are a strong communicator who can translate technical choices into business impact for the Management Team and non-technical stakeholders
- You lead by enabling others — you measure success by what the rest of the organisation can do independently, not only by what your team produces
- You think in systems — you look past individual requests to root causes and antipatterns, design structural solutions, and influence other departments to adopt better data practices
- You are effective in a matrix — you align stakeholders and create consistency across teams that don’t report to you
- You bring structure to ambiguity and can balance a transformation mandate with day-to-day delivery
- You treat governance, quality, and compliance as design principles rather than afterthoughts
Nice to have
- Experience in fintech, brokerage, or another data-rich, regulated environment
- Familiarity with financial or regulatory reporting and frameworks such as BCBS 239, DORA, or GDPR
- Knowledge of financial markets and products such as options and futures
- Experience introducing AI-assisted data access or ML capabilities into an organisation
- Experience setting up self-service BI and data governance from the ground up
What do we offer
- A competitive salary
- a fixed 13th month
- 8% holiday allowance
- a pension scheme fully paid by LYNX
- public transport travel allowance
- home office equipment and home office allowance
- continuous growth potential, including a personal training budget of € 2,000 per year to invest at your own discretion
- daily lunch from our chef, beverages & fruit, Friday drinks at our own bar
- Multiple trips & activities
Who we are
“LYNX helps you invest in yourself.”
“Working at LYNX means joining the LYNX family.”
“The development opportunities make LYNX the best place to work.”
This is what employees say about LYNX — and it reflects exactly what we aim to offer: an environment where you can get the best out of yourself.
From our offices in Amsterdam, Ghent, Berlin, and Prague, we work every day to provide private and professional clients with the best trading opportunities through a fast, user-friendly, and reliable platform.
LYNX is an international FinTech company where around 300 colleagues contribute to client success across Europe in an informal, collaborative, and growth-oriented environment.
We’re an equal-opportunity employer. We welcome applications from all suitably qualified and eligible candidates without attention to gender identity/expression, age, racial, ethnic and cultural background, religion and beliefs, sexual orientation/identity, disability or neurodiversity.
