2 months ago
Gurgaon, IndiaMid Level
Responsibilities
- Design, build, maintain, and optimize scalable data pipelines for analytics, reporting, and AI/ML use cases.
- Lead migration of legacy data architectures to modern cloud-based, AI-ready data platforms.
- Develop semantic layers that provide consistent, business-friendly access to data for analytics and BI tools.
- Collaborate with stakeholders, data scientists, analysts, and product teams to translate data requirements into technical solutions.
- Ensure data quality, integrity, security, and compliance through validation, monitoring, and governance practices.
- Document data architectures, pipelines, and best practices for maintainability and knowledge sharing.
Requirements
- Bachelor’s or master’s degree in Economics, Statistics, Engineering, or a related quantitative field.
- At least two years of hands-on experience with advanced Python and PySpark, including performance tuning and complex query optimization.
- Hands-on experience with data lakes, lakehouses, and data warehouses such as Snowflake, Databricks, BigQuery, or Redshift.
- Snowflake certification at the SnowPro Core level is required; SnowPro Advanced is preferred.
- Experience supporting AI/ML pipelines and feature engineering is desirable.
- Working knowledge of Tableau, Power BI, or Looker is desirable.
- Hands-on experience with AWS, Azure, or GCP is desirable.
- Excellent communication skills and the ability to explain technical concepts to non-technical audiences.
Tech Stack
Categories
Data Engineering
About EXL
EXL provides data analytics, AI, and digital operations services for enterprises in insurance, healthcare, banking, and other regulated industries. It delivers consulting, managed services, and technology platforms to improve decision-making, risk management, and operational efficiency. Founded in 1999 and headquartered in New York, EXL is a public company listed on the NASDAQ (ticker: EXLS).