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EXL

Analyzes business data and runs outsourced operations

Data Management Solution Lead

Data ManagementConfirmed live in the last 24 hours
Full-timeLondon, UK

About the Job

Requirements

  • A Bachelor's or Master's degree in Computer Science, Engineering, IT or a related field, or 10+ years of relevant professional experience.
  • At least 7 years of professional experience designing and delivering enterprise data solutions, including data warehouses, data platforms, data integration and data migration.
  • At least 3 years of experience working with Banking & Capital Markets organisations or Energy, Utilities and Travel organisations, in consulting services or directly in industry.
  • Hands-on experience architecting solutions on at least one major cloud data platform, such as AWS, Azure, GCP, Databricks or Snowflake, including data pipeline and integration design.
  • Strong data modelling capability across conceptual, logical and physical models, with practical experience of data quality, metadata and governance design.
  • A working understanding of AI and generative AI, including how AI solutions depend on data foundations such as data for retrieval-augmented generation and retrieval, metadata and lineage for governed AI use, and how AI capabilities are applied within data management.
  • Experience supporting pre-sales activity in a consulting services organisation, including solution shaping, estimation and contribution to proposals or RFP responses.
  • Experience providing technical leadership to delivery teams, including reviewing designs and guiding engineers.
  • Ability to balance hands-on solution design with the commercial realities of a consulting engagement, including effort, margin, risk and deliverability.
  • Ability to translate complex technical designs into clear options and recommendations for business and technology stakeholders.
  • Ability to present solutions to client architects, senior managers and workshop groups.
  • Ability to build trust and credibility with client technical and delivery stakeholders on aligned accounts.
  • Strong estimation capability, including sizing solutions, teams and timelines with defensible assumptions.
  • Strong analytical skills and ability to draw conclusions from abstract material.
  • Ability to partner across sales, delivery, AI engineering and competency leads to shape and land solutions.
  • Clear written and spoken communication, including high-quality solution documentation.
  • Strong understanding of the strengths and weaknesses of leading data management technologies and tools, sufficient for meaningful discussions with clients and team members.
  • Pragmatic, delivery-minded approach to designing solutions that teams can build and clients can operate.
  • Curiosity about the evolving AI landscape and its implications for data management while maintaining focus on data fundamentals.
  • Must already be eligible to work in the United Kingdom.

Responsibilities

  • Serve as the solution architect on assigned client engagements within aligned accounts, accountable for the technical integrity, scalability and deliverability of the data solutions designed.
  • Design end-to-end data management solutions, including data architectures, platform and lakehouse designs, data pipelines and integration patterns, data models, migration approaches and target-state blueprints.
  • Define and apply standards for data quality, metadata, lineage and governance within engagement solutions, ensuring designs meet client regulatory and security requirements.
  • Understand Banking & Capital Markets clients' priorities, including risk and regulatory reporting, customer insight, legacy platform modernisation and migration, and the data foundations required for AI adoption, and reflect these in solution designs.
  • Ensure solutions are designed for AI readiness, with well-governed and well-described data that generative and agentic AI capabilities can safely and reliably consume.
  • Guide and review engagement delivery teams, including multi-shore engineering teams, providing hands-on technical leadership through design, build, testing and deployment.
  • Conduct architecture and design reviews, manage technical risks and issues, and support estimation and planning for delivery workstreams.
  • Lead solution design for new Data Management opportunities within aligned accounts and the sector, shaping the approach, architecture, delivery model, team shape and estimates for proposals and statements of work.
  • Contribute solution content to proposals, RFI/RFP responses and oral presentations, working with Sales, Engagement Leads and the Interlock Lead.
  • Design and support proofs of concept, demos and technical accelerators that demonstrate data management capabilities to clients and prospects.
  • Participate in client workshops and discovery sessions, translating business challenges into solution options and articulating value, effort and risk.
  • Provide solution assurance on active pursuits by reviewing estimates, assumptions and technical approaches for deliverability and margin.
  • Convert solution designs and engagement experience into reusable practice assets, including reference architectures, solution patterns, estimating models and accelerators.
  • Share knowledge across the practice through design reviews, internal enablement sessions and communities of practice.
  • Keep current with the evolving data and AI technology landscape and share relevant insights with the practice and aligned accounts.
  • Provide technical leadership and day-to-day guidance to engineers and designers on assigned engagements, including reviewing work and coaching on solution quality.
  • Provide feedback to the people managers and competency leads of resources on engagement teams.
  • Perform other duties as assigned or identified.

Desired Qualifications

  • Experience with master data management and data governance frameworks and tooling.
  • Understanding of the data landscape and regulatory context of financial services, including risk and regulatory data, data lineage and BCBS 239-style requirements, customer and counterparty data, and cloud adoption in regulated environments.
  • Experience with large-scale platform migration or modernisation programmes, such as migrating legacy warehouse or analytics estates to cloud.
  • Exposure to AI-native and lakehouse platforms and services, such as Azure AI Foundry, Vertex AI, Bedrock and Databricks, from a data architecture perspective.
  • Relevant cloud or platform certifications, such as AWS, Azure or GCP data or architecture certifications.
  • Knowledge of project delivery methodologies, including Agile and Scrum.

About the Company

EXL

Analyzes business data and runs outsourced operations

EXL analyzes business data and runs outsourced operations for insurers, healthcare payers, banks, retailers, and other large organizations. Its teams combine industry expertise with data engineering and AI to handle tasks such as claims processing, payment reviews, customer service, and finance within existing technology environments. The company also builds software, including LifePRO, which manages insurance policies, and EXLdata.ai, which connects fragmented data for use in AI systems. Clients pay for consulting projects, ongoing managed services, and software delivered through the cloud. EXL was founded in 1999 and is headquartered in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1999

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