Senior Director, Data & Analytics

Responsibilities

• 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
• 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
• 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, SLAs, and lifecycle management
• Discoverability through catalogs and semantic layers aligned to client business domains
• Improve delivery velocity through standardization, reuse, and AI-assisted data engineering practices and AI-enabled accelerators
• Serve as an escalation point and trusted advisor on complex client situations
• Drive adoption of AI across the data lifecycle in client engagements, including:
• Data discovery, profiling, and quality automation
• Metadata management and semantic layer evolution
• Intelligent pipelines and data observability
• Partner with our Product Engineering Capability to ensure:
• Client data platforms reliably support AI/ML and GenAI use cases
• Strong architectural alignment between data foundations and application-layer AI capabilities
• Reusable patterns for feature engineering, ML-ready datasets, and data pipelines supporting AI-driven use cases in client environments
• Serve as Presidio Digital's external voice for Data & Analytics — in client conversations, industry forums, and the broader market
• Develop and drive thought leadership, POV's, and go-to-market narratives on:
• Modern data platforms and cloud-native architectures
• Data-as-a-product and AI-enabled data ecosystems
• Represent Presidio Digital in:
• Client executive briefings and strategic pursuits
• Industry events, webinars, and conferences
• Client workshops and advisory engagements
• Enable internal teams (Sales, Presales, Delivery) with playbooks, collateral, storytelling, and training
• Partner with Sales and Presales to shape data-led transformation opportunities and support strategic pursuits
• Define and package client-facing service offerings, including:
• Data platform modernization
• Data foundation for AI
• Analytics transformation and data product adoption
• Actively contribute to pipeline growth in key accounts through proactive opportunity identification and solution shaping
• Develop proposals, delivery models, and value propositions that are competitive and client-outcome-driven
• Contribute to partner-aligned go-to-market motions in close collaboration with Presidio's Partner Alliance group — including co-sell opportunities, joint account planning, and data-platform-specific partner activations (AWS, Microsoft Azure, Google Cloud, Snowflake, Databricks, Microsoft Fabric)

Requirements

• Bachelor's Degree or equivalent experience and / or military experience
• Overall 10+ years in Data & Analytics with progressive leadership experience, including 3+ years in a senior leadership or Practice leadership role
• Hands-on experience supporting pre-sales, solution shaping, and client-facing GTM motions
• Proven ability to build and scale delivery practices — including accelerators, offerings, standards, and talent
• Experience managing or matrixed leadership over teams of data engineers, architects, and analytics engineers
• Demonstrated track record of leading data platform modernization and analytics transformation engagements in a client-facing / consulting services environment
• Strong foundation in data engineering and modern data architectures (lakehouse, medallion architecture, streaming, domain-oriented design) — hands-on roots that inform architectural judgment and the ability to build breadth across platforms and patterns
• Solid understanding of data governance, data quality, metadata management, and data lifecycle management
• Familiarity with designing data systems that support AI/ML workloads — feature stores, ML-ready datasets, vector databases
• Awareness of AI/GenAI capabilities grounded in data enablement; partnership with AI engineering teams preferred

Preferred Skills

• Relevant platform certifications (Databricks, Snowflake, AWS Data Analytics, Azure Data Engineer) are a plus
• Experience in partner co-sell motions with cloud or data platform vendors
• Prior experience building or scaling a practice within a consulting or technology services firm