Head of Technology, Big Data

Let’s start with the role

As the Head of Technology for Big Data, you will own the technical vision, architectural strategy, and operational execution of Kaizen Gaming's most critical and complex data platform. The division builds and operates the core Data Platform spanning ingestion, streaming, orchestration, and core data transformation (Bronze-to-Gold medallion architecture), which underpins all downstream AI, BI, and business-enabling applications.

You will lead the Data Engineering function across these areas, ensuring our high-scale cloud platforms meet the highest standards of quality, reliability, and compliance across every market in which we operate. This is a senior leadership role and a member of the company’s Management Team. 

Reporting to the Senior Director of Technology, Data and Analytics, you will directly lead a team of 3–7 team leads and a Principal Engineer, while providing leadership to approximately 40–60 people indirectly. You will act as a business enabler, bridging technical complexity with strategic business value. 

 

 

As the Head of Technology, Big Data you will:

 

 

Technology Strategy & Platform Evolution

• Strategic Gap Analysis & Roadmap — Continuously assess the gap between the current state of the Big Data platform and future business needs across capability, efficiency, and organisational maturity. Translate these insights into a technology roadmap and a portfolio of high-impact Proofs of Concept (PoCs). 
• Architectural Stewardship — Own the Data Platform's core ingestion and transformation layers (Bronze to Gold). Identify and communicate architectural risks early, maintain architectural coherence across concurrent initiatives  (including the dbt migration, Dagster orchestration, RisingWave streaming, ADW decommissioning), and ensure Principal Engineers have the context required to make sustainable technical decisions.
• Platform Strategy & Technology Evaluation  — Own the continuous evaluation and evolution of the platform technology stack, making key build-vs-buy decisions based on PoC outcomes and strategic business direction.

 

Leadership & People

• Organizational Leadership & Health — Lead and manage 3–7 Team leads and a Principal Engineer directly, while providing leadership to 40–60 people indirectly. Foster a quality- and performance-centric data engineering culture through a Multipliers leadership approach that promotes team autonomy, psychological safety, and accountability.
• Employee Engagement — Maintain high levels of engagement, morale, and organisational alignment during periods of leadership transition and strategic change, creating an environment that supports innovation, resilience, and low attrition. 
• Talent Development — Identify capability gaps across the teams and design or sponsor targeted training, mentoring, and learning programs (including AI-adoption programs) to strengthen technical capability, support succession planning, and enhance Kaizen Gaming's external engineering reputation. 

 

Stakeholder, Partner & Regulator Management

• Stakeholder & Peer Management — Proactively engage, align, and communicate with senior internal stakeholders (EXCO, Top Management Team, peer Heads across AI, BI and Data Business Enablement, and business sponsors in Finance, Compliance, CRM, and Gaming Operations) and external partners. Ensure divisional priorities are understood and championed at leadership level.
• Partners & Regulators — Manage strategic relationships with major platform partners (including Databricks, dbt Labs, and other technology vendors and SaaS providers ). Partner with Finance and Compliance to meet growing statutory and regulatory audit demands across multiple jurisdictions (such as MGA, PwC, Grant Thornton, MNP, ONJN) with fast, audit-ready data.

 

Financial Stewardship & FinOps

• Platform OpEx Ownership — Own and manage the Data Platform operating expenditure, principally cloud compute (Azure, Databricks), dbt Cloud, and software licenses.
• FinOps Optimization — Accountable for FinOps cost transparency, proactive anomaly detection, and cost optimization to ensure maximum platform efficiency and value.
• Budget Ownership — Manage the department's discretionary budget (training, tooling, bonding) and make hiring decisions within the approved headcount plan.

 

Decision-Making

• Define the long-term technology stack and architecture direction for the Data Platform.
• Prioritise and sequence the department's strategic project portfolio, managing dependencies across multiple concurrent platform transformation initiatives.
• Make high-impact architectural decisions, establishing technical guardrails where systemic risks exist while empowering teams with appropriate autonomy. 
• Allocate platform OpEx and make FinOps optimization decisions within the approved annual operating budget.
• Determine organization and people decisions within your scope, including hiring, team structures, performance evaluations, and development investments.
• Operate with a high degree of autonomy under broad strategic direction, setting annual objectives and contributing directly to longer-term functional and business strategy.

 

 What you will bring

 

 

 Education & Qualifications

• MSc in Computer Engineering, Computer Science or another quantitative discipline. 
• Extensive leadership experience managing multiple, cross-functional Data Engineering teams, with deep expertise in Big Data platforms and data architecture.
• Proven track record of owning enterprise-scale data platforms, designing medallion architecture (Bronze to Gold), developing scalable data models, and leading PoC-driven technology evaluation.

 

Technical Expertise 

• Core Platform & Orchestration: Hands-on experience with Databricks, dbt, Dagster, Apache Spark, SQL, and Python for building and orchestrating scalable data pipelines.
• Streaming & Infrastructure: Practical experience working with Kafka, RisingWave, and Azure in streaming and cloud infrastructure environments.
• Development & Collaboration: Proficiency in Git and CI/CD pipelines, with working knowledge of data modeling/lineage tooling and collaboration platforms such as Jira and Confluence.
• AI Integration: Demonstrated ability to leverage AI tools and assistants to enhance productivity, technical decision-making, architectural design, and leadership effectiveness.

 

Skills & Mindset

• Strategic Problem-Solver — Able to navigate highly complex, ambiguous, and constantly evolving technical challenges through analytical thinking, sound judgment, and creative problem-solving. 
• Multipliers Leadership — Proven ability to lead through collaboration by developing talent, increasing team autonomy, fostering psychological safety, and building high-performing engineering organisations. 
• Cross-Functional Collaboration — Strong influencing and communication skills, with the ability to translate technical and architectural complexity into strategic business value for non-technical stakeholders, auditors, and vendors.
• AI-First Mindset — Actively adopting and championing AI tools and assistants in everyday work, encouraging teams to embed AI into product discovery, delivery, and decision-making, and continuously exploring how AI can improve quality, efficiency, and time-to-market. At Kaizen, leveraging AI tooling is a core way of working, not an afterthought.

Kaizen Gaming Perks

• 💸 Competitive pay and bonus scheme;
• 👩‍⚕️ Private health insurance for you and your family;
• 💰 Monthly meal allowance;
• 🚗 Company Car;
• ⭐ Developmental 360° feedback framework;
• 📚 Unlimited access to Udemy & continuous training;
• 👨‍👩‍👧‍👦 Family Support.
• #LI-MS
• #LI-Onsite