Head of Data and Analytics (Europe)
Role details
Job location
Tech stack
Job description
We are looking for a Head of Data and Analytics to join our Commercial Center of Excellence team. Location is flexible within the EU., The Head of Data and Analytics is responsible for defining and executing the enterprise data and analytics strategy to unlock business value, drive profitable growth, and improve decision-making. This role prioritizes initiatives and investments across the data ecosystem, ensuring clear ROI and alignment, and builds a data-driven culture through governance, enablement, and measurable outcomes. The Head of Data and Analytics collaborates with cross-functional teams, including sales, marketing, finance, and IT, to drive data-driven decision-making and enhance commercial performance.
Strategy and Roadmap
- Develop and own the multi-year enterprise data & analytics strategy and operating model.
- Create value-backed roadmaps, prioritizing use cases, platforms, and capabilities.
- Establish portfolio management and KPI frameworks to track impact and ROI.
Team Leadership
- Build, lead, and mentor cross-functional teams (data engineering, analytics, data science/ML, BI).
- Define roles, career paths, and best practices; foster collaboration with product, IT, security, and business units.
Cross-functional alignment and Governance
- Establish mechanisms to capture inputs and requirements from IT, Security, Product, Finance, Sales, Marketing, and Operations.
- Design and enforce data governance frameworks: data quality standards, privacy, and access
- Chair executive Steering Committees and run Tactical Working Boards to prioritize initiatives, remove blockers, and align on trade-offs.
- Create RACI/decision rights, communication cadences, and escalation paths to ensure transparency and accountability.
- Partner with business owners on value cases, adoption plans, and change management to drive measurable outcomes., * Strategic thinking and prioritization: Balances long-term vision with near-term wins; makes data-informed decisions under ambiguity.
- Change management: Guides org through culture and process shifts; builds advocacy and manages resistance.
- Collaboration and facilitation: Runs effective Steercos/working groups; elicits inputs, mediates conflicts, and secures decisions.
- Customer-centric mindset: Frames problems around user needs and measurable outcomes.
- Coaching and talent development: Mentors teams, fosters psychological safety, and raises performance standards.
- Influential leadership: Aligns senior stakeholders, negotiates trade-offs, and drives consensus without authority.
- Bias for action and accountability: Sets clear goals, follows through, and course-corrects quickly.
- Systems thinking: Connects processes across IT, sales, finance, and operations to optimize end-to-end value streams.
Why Barentz? Barentz is a fast-growing organization with an open culture and short lines of communication. We offer you the freedom and opportunity to operate independently, within the set objectives and frameworks. Barentz is looking for employees who are creative, independent, and energetic, and who like to take on challenges. You like to work in a dynamic and rapidly changing environment, which requires a high degree of flexibility.
Interested? xcskxlj
If you feel excited reading the above and want to join our journey, please send your CV in English by using the button to apply. Any questions regarding this position, please contact Jill Lan
Requirements
- 8+ years in data/analytics; 4+ years leading cross-functional data teams.
- Proven track record in defining and executing enterprise data strategies with measurable ROI.
- Hands-on leadership of data platforms (cloud data warehouses/lakes) and BI modernization.
- Standing up and operating data governance at scale (quality, privacy, access, stewardship).
- Budget ownership, vendor/partner management, and contract negotiation
- Experience in change management and building a data-driven culture across business units.
- Preferred: Delivering advanced analytics/ML use cases from concept to production.
Technical Skills
- Strategy & Portfolio: OKRs/KPIs, value case development, portfolio, and prioritization frameworks.
- Data Architecture: Modern data stack, ELT/ETL, data modeling (star/snowflake), data mesh/data fabric concepts.
- Cloud & Tools: One or more of AWS/Azure/GCP, Databricks/Snowflake/BigQuery/Redshift, dbt, Kafka/streaming.
- Preferred: Analytics & ML: SQL, Python/R familiarity, feature stores, MLOps, experimentation/causal inference basics.
- BI & Visualization: Power BI/Tableau/Looker; semantic models; self-serve enablement.