Senior Director, Data & Analytics

Presidio, Where Teamwork and Innovation Shape the Future
At Presidio, we're at the forefront of a global technology revolution, transforming industries through cutting-edge digital solutions and next-generation AI. We empower businesses - and their internal customers - to achieve more through innovation, automation, and intelligent insights.

The Role

Presidio Digital is seeking a Director / Senior Director, Data & Analytics to lead and scale our Data & Analytics Practice into a modern, AI-enabled capability that drives real client outcomes. This is a player-coach leadership role: you will set the strategic direction while staying close enough to client engagements and delivery to make it real.

You will operate at the intersection of capability building, client delivery, market growth, and people leadership — shaping how we design, build, and scale data platforms and data products for enterprise clients across industries, while attracting, developing, and inspiring a high-performing team of data professionals. You will partner closely with Sales, Presales, and adjacent Delivery capabilities (Product Engineering and Solution / Product Ownership)  to ensure we deliver differentiated, outcome-driven data solutions at speed and at scale.

Why This Role Matters:  This role is about building the data foundation that powers AI transformation for our clients. If you want to shape a growing practice, win in the market, and leave fingerprints on the next chapter of what a modern data services organization looks like — this is the role. You are personally passionate about the potential of AI-ready data platforms to transform how enterprises operate and deliver business outcomes, and you bring that conviction to every client conversation, every pursuit, and every interaction with your team. 

The right person for this role thrives in a fast-moving, high-energy environment where priorities shift and ambiguity is part of the landscape. The leaders who succeed here lean into that energy — be resilient, composed under pressure, and genuinely energized by complexity and pace. Equally important is a collaborative, partnership-first mindset — this role sits at the intersection of Sales, Pre-sales, Delivery / Engineering, client stakeholders, and vendor partners, and success depends on building trust across all of them. We win together: client wins, practice wins, and business wins reinforce each other, and this leader is expected to champion that win-win-win orientation in every engagement.

Responsibilities Include:

Capability Leadership & Strategy

• Define and lead the Data & Analytics Practice vision, growth strategy, and multi-year roadmap
• Drive evolution from traditional data warehousing to:
  • Modern data platforms (lakehouse, real-time, domain-oriented architectures)
  • AI-enabled data ecosystems built for production-grade analytics and AI workloads
  • AI-enabled data products that deliver governed, reusable, and business-aligned data assets at scale

• Establish standards and best practices across data engineering, modeling, architecture, governance, quality, and lifecycle management
• Shape how the Practice differentiates in the market through offerings, accelerators, and delivery models
• Act as the Practice's executive voice internally — influencing investment decisions, headcount plans, and strategic priorities

Client Delivery Excellence & Data Product Acceleration

• As a client-services organization, delivery is core to our identity. This pillar is not a support function — it is a primary accountability.
  • Provide active oversight and quality assurance on key client engagements, ensuring:
    • Strong architecture, scalability, and alignment to client business outcomes
    • Consistency in delivery approach, data product thinking, and engineering quality
• Build and scale reusable delivery accelerators, including:
  • Ingestion frameworks for batch, real-time, and event-driven pipelines
  • Data quality and observability toolkits
  • Reusable data products: curated datasets, semantic models, and feature-ready datasets
  • Standardized data models and transformation pipelines

• Drive adoption of data-as-a-product principles across client engagements:
  • Clear ownership, SLA