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EXL

Analyzes business data and runs outsourced operations

Agentic Data Delivery Lead

Engineering LeadershipConfirmed live in the last 24 hours
Full-timePune, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 20 years of IT experience, with a strong early-career foundation in solution development or engineering.
  • At least 10 years of experience in data engineering and platform delivery, including data lake or data warehouse implementation, on-premises-to-cloud or cloud-to-cloud migration, platform modernization, and digital transformation.
  • Three to four years of hands-on experience delivering generative AI or agentic AI solutions.
  • Experience building and leading large delivery teams and Centres of Excellence.
  • Experience in stakeholder management and global client engagement.
  • Experience with requests for proposals, requests for information, and large-deal solutioning.
  • Mandatory technology exposure includes Python; extract, transform, and load or extract, load, and transform; big data frameworks including Spark and the Hadoop ecosystem; Snowflake; Databricks; lakehouse architectures; AWS, Azure, or Google Cloud Platform; large language models; retrieval-augmented generation; agentic frameworks; and orchestration tools.

Responsibilities

  • Lead end-to-end delivery of large-scale data engineering and modernization programs, including data lakes, data warehousing, lakehouses, and data migration.
  • Define and drive agentic AI-led delivery models to improve productivity across the software development lifecycle.
  • Own delivery governance, quality, timelines, and client satisfaction across multiple accounts.
  • Drive enterprise data transformations, including on-premises-to-cloud migrations, cloud-to-cloud transformations, legacy data warehouse modernization to lakehouse or warehouse platforms, and platform modernization and digitalization initiatives.
  • Architect scalable, resilient, and future-ready data ecosystems.
  • Lead the design and implementation of agentic AI and large-language-model-based solutions in enterprise data ecosystems.
  • Define delivery patterns for multi-agent systems, retrieval-augmented generation pipelines, automation, and intelligent workflows.
  • Drive adoption of AI-led accelerators across delivery programs.
  • Lead requests for proposals, requests for information, and proactive solutioning for large deals.
  • Build value-led proposals, including solution architecture, costing, and delivery models.
  • Work with sales and account leadership on deal shaping.
  • Build, scale, and run Data, AI, and agentic AI Centres of Excellence.
  • Define frameworks, accelerators, reusable assets, and best practices.
  • Develop internal capability maturity models and delivery standards.
  • Define and enforce enterprise-wide data governance frameworks covering data quality, lineage, metadata, and access controls.
  • Ensure compliance with regulatory requirements, data privacy, including personally identifiable information, and security standards across data and AI platforms.
  • Embed governance controls within data engineering pipelines and agentic AI or generative AI delivery workflows.
  • Establish standards for data lifecycle management, audit readiness, and risk mitigation.
  • Implement AI governance practices, including model oversight, ethical AI usage, and guardrails.
  • Collaborate with stakeholders to drive adoption of governance policies across global delivery teams.
  • Engage with senior client stakeholders at CXO and VP levels.
  • Advise clients on data strategy, AI adoption, and digital transformation.
  • Manage multi-geography teams and global client engagements.
  • Drive strategic partnerships with hyperscalers and technology partners, including AWS, Azure, Google Cloud Platform, Snowflake, Databricks, OpenAI, Anthropic, and generative AI ecosystem providers.
  • Influence joint go-to-market strategies and co-innovation initiatives.
  • Lead and mentor large cross-functional delivery, architecture, and engineering teams.
  • Build leadership pipelines and a strong engineering culture.
  • Drive team performance, engagement, and capability development.

Desired Qualifications

  • Experience with multi-agent architectures and AI-driven automation of the software development lifecycle.
  • Exposure to MLOps, DataOps, and AI governance frameworks.
  • Experience in insurance, banking, healthcare, or retail.
  • Thought leadership through whitepapers, points of view, or client presentations.

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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