Vice President, Global Data Platforms

About the role

The Vice President, Global Data Platforms is a senior leader in Aristocrat's Enterprise Data & Analytics (ED&A) organization. They are accountable for defining and leading the global strategy, delivery, and operational excellence of enterprise data platforms.

Responsibilities

• Define and drive the global data platform strategy ensuring aligned, scalable, secure, and cost-effective platforms.
• Communicate strategy, progress, and outcomes to executive leadership.
• Foster consensus and guide investment decisions focusing on value, prioritization, and cost efficiency.
• Proactively engage and influence business and IT leaders to shape data and platform direction for new initiatives, driving modern, scalable approaches over legacy patterns.
• Guide platform and data decisions that enable self-service, data literacy, and improved productivity, in partnership with Architecture and Governance.
• Establish and implement the technical roadmap for data platform modernization, AI-ready data and data capabilities in alignment with enterprise architecture, including the use of AI to improve engineering efficiency.
• Sure data platforms are AI-ready, providing high-quality, well-structured, and discoverable data to support advanced analytics and machine learning.
• Collaborate across data, technology, and business teams to provide platform capabilities and data solutions.
• Establish clear operating models, roles, and decision frameworks to enable consistent execution, including standardization across platforms, technologies, and regions.
• Ensure high availability, performance, security, cost efficiency, and reliability of data platforms in line with organizational and high-impact client-driven and regulatory SLAs.
• Drive engineering and operational excellence by establishing automated and AI-enabled practices that ensure data quality, reliability, and speed of delivery within data platforms.
• Lead and develop a global organization of platform, engineering, and operations leaders and engineers, fostering accountability, collaboration, innovation, and continuous improvement.

Requirements

• 15+ years leading large-scale data platform or data engineering organizations, with a track record of delivering measurable business impact.
• Strong executive communication skills, with the ability to influence, drive alignment, and secure consensus for platform strategy and investments.
• Proven ability to define and implement strategic plans, drive technology alignment, and lead large-scale platform transformation initiatives.
• Deep technical expertise in modern data platforms and architectures (e.g., Snowflake, Databricks, Azure, GCP).
• Enablement of AI/ML use cases through data platforms, building AI-ready data foundations and using intelligent tools for engineering efficiency.
• Experience Leading high-performing engineering organizations, including encouraging an environment of responsibility, operational excellence, and ongoing improvement.
• Demonstrated success operating in high-SLA, client-facing environments, including implementing proactive, automated processes to ensure reliability, compliance, and performance at scale.
• Proven ability to collaborate effectively across data functions (e.g., Governance, Architecture, Product, Analytics, Data Science) and business partners to deliver aligned, high-impact outcomes.
• Ownership of platform financials, including budgeting, investment planning, and cost optimization.
• Experience managing strategic vendor and partner relationships, including contract oversight and performance.

Qualifications

• Master's degree in Computer Science, Engineering, Statistics, or related field.
• Professional certifications in data management, data science, or related fields.
• Experience with data warehousing, data modeling, and data governance.
• Knowledge of cloud platforms (AWS, Azure, Google Cloud Platform).
• Experience with data integration tools (ETL, ELT).
• Experience with data visualization tools (Tableau, Power BI).
• Experience with data engineering tools (Apache Spark, Flink, Kafka).
• Experience with data security and privacy best practices.
• Experience with data analytics and machine learning.
• Experience with data platform automation and orchestration.

Skills

• Data platform design and architecture.
• Data engineering and data science.
• Data governance and data management.
• Data security and privacy.
• Data analytics and machine learning.
• Data platform automation and orchestration.

Benefits

Comprehensive benefits package including health, dental, and vision insurance, paid time off, and a 401(k) plan with employer matching. Details available at https://atibenefits.com/.

Pay

$192,500 - $357,500 per year.

Schedule

Full-time.