Data Lead

Tech Rise; Amsterdam; Hybrid; EUR 110,000 - 170,000; Full time

Job summary

Tech Rise is seeking a Data Lead in Amsterdam to own the data function end-to-end, overseeing the operating model, platform investments, and a team of ~5 engineers/analysts. You will collaborate with Product, RevOps, Finance, and GTM to centralize data and demonstrate the impact of the product on business performance.

You will design the internal data stack, set data standards, and drive governance, ensuring a single source of truth for critical metrics while guiding analytics, AI readiness, and

Qualifications

• 7+ years in data or analytics roles, with leadership experience.
• Experience designing and building core data stacks (warehouse, pipelines, BI).
• Strong SQL skills and hands-on with modern data tools (Snowflake, Databricks, dbt...).
• Ability to partner with RevOps, Security, Engineering and Finance to align data with business priorities.

Responsibilities

• Own the design and implementation of the internal data stack — warehouse, pipelines, orchestration, and BI layer.
• Define target architecture compatible with the existing external product data stack owned by the reporting team.
• Safeguard data quality, reliability, and documentation across all critical datasets.
• Create and maintain shared metric definitions and data standards across the business.

Skills

Data leadership

SQL

Modern data stacks

Stakeholder management

Tools

Snowflake

Databricks

dbt

Azure Data Factory

Fivetran

Power BI

Looker

Job description

Location: Amsterdam, Netherlands (Hybrid)

Reports to: CTO

About the Role

As Data Lead you'll own the data function end-to-end: the operating model, platform investment, team and outcomes. You'll lead an engineering team (~5 FTE), working closely with Product, RevOps, Finance and GTM to make data central to how the business operates day-to-day. The ambition is to tie operational data to engagement results so that customers can prove the impact of their core product on business performance.

What You'll Be Doing

• Own the design and implementation of the internal data stack — warehouse, pipelines, orchestration, and BI layer
• Define target architecture compatible with the existing external product data stack owned by the reporting team
• Safeguard data quality, reliability, and documentation across all critical datasets
• Create and maintain shared metric definitions and data standards across the business

Strategy & Stakeholder Leadership

• Define and own the company's data strategy and 12-month roadmap, aligned to company OKRs
• Partner with leadership — including RevOps, CISO, CTO, Finance, and Product — to align data capabilities with business priorities
• Establish clear working agreements with RevOps on metric ownership and shared data models, ensuring a single source of truth for critical company metrics
• Work alongside the CISO on data governance and access controls — security policy remains with the CISO; implementation sits with the Data Lead

Analytics & AI Readiness

• Deliver self-serve BI capabilities for Product, Customer Success, Finance, and the executive team
• Own product and customer engagement metrics; collaborate with RevOps on a shared revenue metrics layer
• Ensure data is structured, documented, and governed in ways that enable advanced analytics, automation, and AI use cases
• Set the standard for how the team uses LLMs, agents and automation in daily work, leading by example through hands-on workflow development
• Lead, coach and develop a team of ~5 data engineers and analysts
• Foster a data-driven culture across the organisation through standards, tooling, and stakeholder engagement

What We're Looking For

• 7+ years in data or analytics roles, with at least 3 years in a leadership or management capacity
• Proven track record of building or rebuilding a core data stack — warehouse, pipelines, orchestration, BI layer, semantic models, and shared metric definitions — in a way the business actually adopts
• Strong SQL skills and hands-on experience with modern data stacks: Snowflake or Databricks, dbt, Azure Data Factory, Fivetran, Power BI or Looker
• Experience operating in ambiguous, fast-growing environments where ownership is unclear and priorities shift
• Demonstrated ability to work as a peer alongside RevOps, Security, and Engineering — influencing without formal authority
• Pragmatic, analytical, and results-oriented — able to turn complex data challenges into clear priorities and tangible outcomes
• Understanding of data privacy, security, and governance in enterprise environments