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Location
In office (Gurgaon)
Seniority
Junior · 2+ years exp

Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Oct 15, 2026. EXL scores B on the Alion truth index.

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EXL

EXL, legally ExlService Holdings, is a data analytics, AI and digital operations company headquartered in New York that runs outsourced business processes and builds data and AI solutions for insurers, healthcare organisations, banks, media and retail companies. Founded in 1999 and listed on Nasdaq, it has more than 60,000 employees across six continents, with large delivery centers in Noida, Gurgaon, Pune, Bengaluru and Chennai and a newer AI hub in Dublin. It hires data scientists and data engineers, GenAI and MLOps engineers, analytics managers, solution consultants and client partners, plus talent acquisition, finance and medical coding staff.

Cloud Engineers design, deploy, and manage cloud infrastructure solutions. Responsibilities include configuring cloud services, optimizing performance, and ensuring security. You will collaborate with other IT professionals to integrate cloud solutions with existing systems. Proficiency in cloud platforms and strong problem-solving skills are required.

Highly motivated data and analytics engineer to support actuarial and business stakeholders by delivering scalable data solutions, automating manual processes, and driving modernization initiatives across analytics platforms. The role will involve close collaboration with actuarial teams, underwriters, business stakeholders, data engineers and technology teams to streamline data workflows, migrate analytical assets, and improve operational efficiency through automation and cloud-enabled solutions.

The ideal candidate should possess strong, analytical skills, experience working with large datasets, cloud platforms, reporting, tools, and a passion for transforming manual processes into automated and scalable solutions.

Design and implement cloud solutions, Optimize cloud infrastructure for performance and cost efficiency, Ensure cloud solutions meet security and compliance standards, Provide technical support for cloud environments, Collaborate with stakeholders to address cloud needs.

  • Collaborate with actuarial, underwriting, finance, and business stakeholders to understand analytical requirements and translate them into technical solutions
  • conduct requirement gathering sessions, deine and document functional and technical specifications
  • identify opportunities to automate manual reporting, data preparation, reconciliation and validation processes
  • design and implement automated workflows to improve operational efficiency and reduce turnaround times
  • develop reusable frameworks and standardized processes for recussing analytical activities
  • drive continuous improvement initiatives focused on reducing manual effort and enhancing data reliability
  • Migration of data assets, analytical codes, reports, and workflows across platforms and technologies
  • support migraiton initiatives involving AWS, data warehouses and reporting tools
  • analyze existing processes and recommend modernization approaches to improve scalability and maintainability
  • build and maintain robust data pipelines for ingestion, transformation, and delivery of analytical datasets
  • optimize data processing and storage strategies to improve performance and scalability
  • Bachelor Degree in relevant field with 2 - 6 years of relevant experience
  • Experience in Data analytics, data engineering or related roles
  • Experience working with insurance domain or financial services
  • Strong SQL, python and data manipulation skills
  • Experience with cloud platforms preferably AWS
  • Knowledge of CI/CD and analytics deployment best practices, github
  • Experience with data migrations, platform modernization, or cloud transformation initiatives
  • excellent problem solving and communication abilities
  • Preffered
    • Experience in Property & Casualty, Life, ReInsurance domains
    • Experience with SAS, R, PySparK, VBA
    • experience with ELT.ETL tools and modern data platforms
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