Director Of Engineering, Data & AI Platforms

Director Of Engineering, Data & Ai Platforms

Xplor is seeking a visionary leader to join as our Director of Data & AI Platforms. In this critical role, you will be responsible for defining and executing the strategy that transforms data into a core enterprise asset and a driver of commercial value through advanced analytics and AI. You will lead and expand a talented team of data architects and engineers to build, scale, and optimize our enterprise data and AI platform, architected around Snowflake and modern data transformation frameworks.

The ideal candidate is a results-oriented data leader with a proven track record of building and leading technical teams in a high-growth, fast-paced environment. You are passionate about "closing the gap between ambition and action" by transforming raw data into reliable, accessible, and valuable products—from curated datasets to predictive models and Generative AI applications—that empower internal decision-making and create new revenue opportunities. This role demands a unique blend of deep technical expertise, strategic product thinking, financial acumen, and inspirational leadership.

Roles and Responsibilities

• Strategic & Commercial Leadership: Develop and execute a comprehensive vision for Xplor's Data and AI strategy. Champion "data as a product," identify opportunities for data monetization, and drive initiatives that create measurable business value through advanced analytics, machine learning, and Generative AI.
• Team Development & Mentorship: Lead, mentor, and grow a high-performing team of Data professionals. Foster a culture of accountability, innovation, and continuous improvement aligned with business objectives.
• Modern Data & AI Stack Architecture: Break down data silos by designing and implementing a unified data architecture. Standardize data ingestion from disparate sources (APIs, event streams, databases) and orchestrate robust data and ML pipelines to ensure the entire ecosystem is efficient and cost-effective.
• Data & AI Productization: Drive the data product strategy from conception to launch. This includes delivering curated, business-ready data sets for self-service analytics, as well as developing and deploying production-grade predictive models and AI-driven applications.
• Financial & Performance Management: Own the budget for the data and AI platform and team. Meticulously manage platform costs and demonstrate a clear return on investment (ROI) for all data and AI initiatives.
• Data Governance & Quality: Establish and enforce a pragmatic data governance framework that ensures high levels of data quality, security, privacy, and compliance. Implement tools and processes for data and model quality monitoring.
• Execution & Delivery: Lead the team in the execution of automated and scalable data integration, transformation, and modeling processes using modern data transformation frameworks (e.g., Spark, Coalesce, dbt).
• Cross-Functional Collaboration: Act as the key data and AI stakeholder, collaborating with executive leadership, product management, and engineering teams to translate business needs into technical requirements and data-driven strategies.