VP Architecture - Data Management

Are you skilled at building client relationships and delivering impactful Data Management solutions? Are you passionate about data? As an EXL VP of Data Management - Architecture, you will lead requirements, data modeling, data movement, transformation mapping, automation, testing, and solution design aligned to enterprise data standards. You will oversee large, complex EDM projects across Data Platforms and Architecture, Data Governance, Data Quality, Data Engineering, Reporting, Analytics, and Data Visualization. This role is strategic and tactical: you will select fit-for-purpose technologies, shape client solution visions, guide technical teams, and support business development by securing and growing client relationships. Who will you work with? This role works closely with client business and IT stakeholders, project teams, EXL Vertical Leads, Engagement Managers, and technical consultants across business analysis, data, cloud, engineering, reporting, and analytics. Why Join EXL? VPs of Data Management - Architecture work on high-visibility projects with measurable client impact. · Business hours vary by client time zone, with occasional early or late meetings for multi-shore teams. · Some U.S. client-site travel may be required; most work is remote using collaboration and video tools. On any one day you might Communicate with Account Executives and clients regarding scope and prioritization of work. Collaborate with Analysts, Data Architects, and Engineers to improve processes and resolve issues. Coach/mentor a team member by providing feedback to elevate their performance. Support SOWs, RFPs, estimates, and resource planning for clients. Support internal projects, training, documentation, and delivery methodology improvements. Conduct assessments, discovery, proofs of concept, and technology evaluations. Lead technical delivery at any stage of a project. 60% Client Management, Delivery and Growth Manage key clients with Sales, Vertical Leads, and Engagement Managers to meet revenue goals, ensure satisfaction, grow services, and cross-sell solutions. Serve as primary liaison for client sponsors, maintain key relationships, understand client strategy, and represent the client voice within EXL. Map client needs to relevant products, services, and custom solutions; lead solutioning to deliver the right value proposition. Partner with Sales to expand, upsell, and deliver new solutions to existing and new client contacts. Collaborate with client stakeholders to plan and execute data strategies tailored to varied industries and contexts. Evaluate and implement data management tools; manage vendor relationships for projects or clients. Build rationale for client Data Management initiatives and position teams for implementation work. Facilitate Data Management meetings and workshops. Help technical leads and developers resolve business and data questions. Coordinate with Project Managers and participate in project planning. Analyze feasibility, scope projects, and prioritize deliverables with Project Managers. Liaise between business units, technology teams, and support teams. Support presales activities by: Participating in prospect/client meetings Crafting and delivering content/presentations Developing engagement proposals and responding to RFP’s Creating solution cost estimates, TCO, and resource plan Conducting product demos 30% Capability Growth and Leadership Grow EXL Data Management capabilities through best practices, new offerings, thought leadership, sales support, and junior consultant coaching. Oversee data management tool vendor relationships and align them to EXL methodologies and standards. Apply Data Management expertise to win new work and grow existing clients. Develop and implement innovative thought leadership and techniques using generative AI. Manage direct team members. Provide leadership support (including escalation) and coaching to other team members. Support recruiting through technical and non-technical interviews and hiring feedback. 10% Other duties as assigned or identified Education & Experience 15+ years of Enterprise Data Management experience 10+ years of consulting experience strongly preferred 7+ years of experience working collaboratively and/or leading global teams Must have practical experience in the following areas: Experience with modern database platforms, such as Snowflake and Databricks, for large-scale data and analytics solutions. Knowledge of implementation best practice and reference architectures Cloud architecture and implementation focused on Data Management and building repeatable patterns Experience with cloud services such as security, access management, networking, monitoring, DevOps, and cost management. Design and implementation experience in Data Architecture, Data Engineering, Data Governance/Quality, MDM, Cloud Architecture, or related pillars. Experience with a programming or scripting language and performance optimization. In depth understanding of various API constructs. Experience with Big Data best practices and the Hadoop technology stack. Experience implementing a form of streaming or messaging technologies. Required understanding of ETL, ELT, CDC, data warehousing, data marts, pipeline orchestration, and enterprise scheduling. Strong SDLC knowledge, including CI/CD, data pipeline automation, and deployment strategies. Experience working with business and IT functions across corporate cultures as an employee and consultant. Experienced working in centralized and federated corporate structures Strong communication skills, with the ability to translate complex technical and business concepts. Strong experience in interviewing and group facilitation. Knowledge, Skills & Abilities Strong executive presence and trusted-advisor skills. Excellent written, verbal, and presentation skills. Expertise with AWS, Azure, Google Cloud, Snowflake and Databricks platforms Demonstrate critical thinking, logical and analytical problem-solving. Ability to research and learn new technologies and processes quickly Ability to assess architectures and recommend improvements. Ability to Architect solutions based on customer requirements Lead small teams while navigating politics in large client environments. Ability to multi-task, prioritize and meet aggressive deadlines. Ability to travel for client engagements. Knowledge of agentic and generative AI patterns for Data Management, including RAG, semantic search, vector stores, knowledge graphs, and enterprise knowledge bases. Ability to design secure, governed, auditable data architectures for AI agents and authoritative data access. Experience with AI-enabled data quality, metadata enrichment, lineage discovery, anomaly detection, and pipeline remediation. Understanding of responsible AI practices, including guardrails, evaluation, human review, observability, cost management, and traceability. Ability to advise clients on AI readiness, governance maturity, data quality, operating models, and high-value use cases. Base Compensation Range: $200-250k The posted range is the hiring range for this role — a subset of the broader range available to employees over time — and reflects base salary across our national hiring scale. Final offers are based on several factors, including the candidate's skills and experience, internal pay equity, work location, market conditions for the role, and the specific scope and responsibilities of the position. The top of the range is reserved for candidates who notably exceed the requirements; the lower end applies to those with less experience or fewer preferred qualifications. For positions based in higher-cost zones (e.g., California, New York, New Jersey), actual compensation may exceed the posted range; your recruiter will share specifics during the process.