Job Description
Unify the data. Unlock the intelligence. Shape ZURU's future!
About ZURU
ZURU is on a mission to disrupt across industries, challenge the status quo and catalyst change through radical innovation and automation advances. This is in play in different pillars of the company: ZURU Toys are re-imagining what it means to play; ZURU Tech is shaping a better future by leading the next building revolution; ZURU Edge is pioneering new generation FMCG brands to better serve modern consumers.
Founded in 2003 by EY Entrepreneur of the Year and World Entrepreneur Hall of Fame brothers Nick and Mat Mowbray, ZURU has quickly grown to a team of over 5000 direct and indirect members across more than 30 international locations.
One of the largest toy companies in the world, globally recognised and award-winning brands include Bunch O Balloons, Mini Brands, XSHOT, Rainbocorns and Smashers. Our global FMCG brands include MONDAY Haircare, Rascals, NOOD, BONKERS, Gumi Yum Surprise, and more!
For more information, visit www.zuru.com.
Position Overview
Lead ZURU's data platform and products teams to deliver measurable business outcomes across Toys, Tech, and Edge divisions. You'll directly manage the Platform team (Databricks, AWS, Fivetran, orchestration) while driving the Data Products team to ship weekly value to the ZURU. You ship in weeks not months, measure impact not dashboards, enable teams to self-serve, and kill what doesn't work.
Position Impact
First 2 weeks: Assume platform ownership (Databricks migration in-progress, AWS SSO, Fivetran connectors). Understand products roadmap (dashboards, pipelines, stakeholder needs). Identify top 3 business blockers.
First month: Ship 1-2 quick wins. Establish weekly ship report cadence with teams. Directly manage Platform team's immediate priorities. Build relationships with key stakeholders across the business.
First quarter: Data Products team shipping measurable weekly value (time saved, decisions improved, not just dashboards). Platform team has dev/prod separation complete and Databricks migration stabilized. You've made 30+ fast decisions, gotten 20+ right, learned from the rest. Federated model operating: platform provides paved roads, domain teams self-serve.
By month six: Data Products team recognized by BU stakeholders as high-impact partner. Platform infrastructure stable and governed (99.5%+ uptime). You own Databricks/AWS/Fivetran deeply enough to mentor Platform team members. You've killed 2-3 low-impact initiatives and doubled down on what works. Composable data stack in place and budling tu support ZURU’s data and AI ambitions.
Roles & Responsibilities
Lead Data Teams Toward Business Outcomes – You own the Data Platform team end to end, including core infrastructure such as Databricks lakehouse, Fivetran connectors, AWS SSO, and orchestration. You are expected to stay hands-on with architecture decisions, code and design reviews, and technical mentorship. The goal is to ensure the platform enables true self-service and never becomes a bottleneck.
Drive Federation, Not Centralisation – The platform team provides shared capabilities such as the lakehouse, governance, and paved roads, while business unit teams own their own data products, dashboards, and analytics. Clear boundaries are critical: platform owns integration layers like connectors and APIs, while BU teams own operational definitions, schemas, and domain understanding. The aim is to enable at least 80% self-service across business units.
Ship Incrementally, Learn Fast – Work in short cycles and default to MVP delivery within 2 to 3 weeks rather than long, complex roadmaps. Validate with one business unit first before scaling to others. Actively stop initiatives that do not demonstrate measurable impact within 4 to 6 weeks. Operate with a strong bias for rapid, reversible decisions, prioritising speed and learning over perfection.
Measure Impact, Not Output – Focus on business outcomes rather than technical deliverables. Avoid measuring activity such as dashboards built or pipelines created. Instead, track time saved, decision quality improvements, forecasting accuracy, adoption rates, and user satisfaction. Every data product should demonstrate measurable impact within two months or be retired.
Build Composable, Not Monolithic – Design systems that are modular, open, and adaptable to change, avoiding vendor lock-in and unnecessary complexity. Continuously simplify and rationalise the stack while ensuring scalability. Work closely with data teams to build foundations that evolve rather than hard-code long-term constraints.
Enable Self-Service Without Bureaucracy – Prioritise documentation and paved roads over support tickets and custom builds. Aim for 95% or more of data access requests to be auto-approved through clear governance rules. The platform team should spend minimal time on individual BU support, and repeated hand-holding is a signal of either tooling or capability misalignment.
Govern Without Slowing Down – Security, privacy, and compliance are non-negotiable, but governance should enable speed rather than restrict it. Use lightweight documentation for MVPs instead of heavy processes. Build frameworks that allow safe acceleration through standards, automation, and clear guardrails, while avoiding unnecessary bottlenecks.
Partner Across Business Units – Build credibility through delivery rather than intent. Stakeholders should experience value shipped, not plans discussed. Maintain weekly engagement with BU stakeholders and start from business problems rather than data solutions. Be willing to challenge and stop low-value work to protect focus on high-impact outcomes.
Develop Talent and Build Capability – Actively manage and mentor the data engineering team, building a high-density talent environment where strong experts lead other experts. Prioritise capability growth through hiring, coaching, and restructuring where needed. Encourage experimentation, learning from failure, and continuously closing skill gaps within the team.
Tools & Technologies (Must Know)
Cloud: AWS (S3, IAM, MWAA Airflow, ECS etc)
Data tools: Databricks, Delta, Notebooks, SQL, Fivetran, DBT, Airflow, PowerBI, Terraform,
Skills & Experience
5–10 Years Leading Data Teams for Business Outcomes – Leads 10–20 person data teams focused on measurable business impact, not output. Proven ability to reduce time-to-insight and connect work to outcomes, not dashboard volume.
Data Product Management – Treats data as products with clear users and measurable value. Starts from business problems, not tools. Willing to stop work that doesn’t deliver impact.
Federated Ownership Model Experience – Builds hub-and-spoke models where platform enables and domains own delivery. Knows when to centralise vs decentralise and enables strong self-service.
Bias Toward Speed and Experimentation – Ships MVPs quickly, iterates fast, and makes reversible decisions without delay. Comfortable killing initiatives that don’t work early.
Hands-On Technical Leadership – Strong technical grounding to guide architecture and engineering decisions (SQL, Python, data modelling, pipelines, cloud). Not daily coding, but can review, unblock, and raise engineering quality.
LIFE@ZURU
At ZURU, we have cultivated a high-performing culture that encourages excellence. Our team works towards ambitious goals, learning, performing, and improving together, all while having fun. We empower talented individuals to do their best work every day.
At ZURU, you get out what you put in. You are responsible for driving your own career and we provide the platform to achieve it. As ZURU is on such a fast growth trajectory, there are opportunities here that you won't find anywhere else.
We recognise that ZURU's success stems from our people and you can only be at your best when you are looking after yourself. ZURU encourages all our team members to invest in their wellbeing by providing an array of benefits and tools.
WHAT WE OFFER
🌱 Culture for Growth 💡 Surrounded by an A Player Team 💰 Competitive Remuneration
ZURU – Tomorrow Reimagined 🚀 ZURU.com
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