E

EXL

Analyzes business data and runs outsourced operations

Lead Data Engineer - Data Modeler

Data EngineeringConfirmed live in the last 24 hours
Full-timePune, Maharashtra, IndiaNo salary listedIn-person

About the Job

Requirements

  • 10+ years of experience and a bachelor’s degree in Computer Science, Information Systems, or related field; or equivalent experience
  • Strong expertise in data modeling (dimensional modeling, warehouse design, normalization techniques)
  • Proven experience designing and implementing data models in centralized/cloud data warehouses (Databricks, Snowflake, Redshift, etc.)
  • Solid experience in data engineering and pipeline development to support modeled data layers
  • 5+ years of experience with Databricks and DBT
  • Experience with orchestration tools such as Airflow or Dagster
  • In-depth experience with distributed systems such as Spark
  • Strong programming skills (Java, Scala, Python) with experience building production-grade data pipelines
  • Experience with AWS cloud services (EC2, EMR, RDS)
  • Strong understanding of data standardization, data governance, and data quality best practices
  • Experience with Git, JIRA, Jenkins, and CI/CD pipelines
  • Experience working with cross-functional teams in a dynamic environment
  • You are passionate about data modeling and designing scalable, well-structured datasets
  • You are equally comfortable implementing pipelines that bring those models to life
  • You think in terms of data consistency, reusability, and long-term maintainability
  • You value clean design, simplicity, and high-quality engineering practices
  • You have a track record of delivering reliable, well-modeled, production-ready data solutions

Responsibilities

  • Design, develop, and maintain scalable, high-quality data models in a centralized data warehouse (primary focus)
  • Translate business requirements into well-structured, reusable data models that support analytics and downstream applications
  • Define and enforce data modeling standards, naming conventions, and best practices across domains
  • Lead and contribute to data standardization initiatives to ensure consistency and interoperability of data assets
  • Build and maintain data pipelines that support and operationalize data models (ingestion, transformation, and delivery)
  • Develop pipelines that transform raw data into clean, well-modeled, analytics-ready datasets
  • Collaborate with Product, Engineering, and Program teams to deliver end-to-end data solutions (models + pipelines)
  • Optimize data models and pipelines for performance, scalability, and cost efficiency
  • Implement processes for data validation, quality monitoring, and reliability
  • Write high-quality, testable code; adopt TDD and contribute to engineering documentation and best practices
  • Perform root cause analysis on data and pipeline issues to improve system robustness

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

Recently Posted Jobs

Explore more opportunities at EXL

See more jobs