Cloud Data Engineer
EXL (company site, opens in a new tab)3–6 yrsGurugramHybridDirect career pageEst. 9–18 LPA
Posted on 8 Sept
Reach people at EXL
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at EXL you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, develop, and maintain scalable data pipelines and workflows primarily using Azure and Databricks technologies to support enterprise reporting and analytics.
- Implement data validation, monitoring, and troubleshooting mechanisms to ensure data accuracy, integrity, and high availability.
- Collaborate with cross-functional teams to support insurance domain use cases, ensuring compliance with data governance and regulatory requirements.
Minimum Requirements
- 3-6 years of experience in Data Engineering with hands-on expertise in Databricks and Azure Cloud technologies.
- Bachelor’s degree in Computer Science, Information Technology, or related field.
- Strong proficiency in PySpark, Python, SQL; experience with Azure Data Factory, Azure Databricks, Azure Data Lake, Delta Lake, and data modeling.
- Experience with ETL/ELT pipeline development, automation, performance tuning, and familiarity with Agile methodologies (scrum, sprint planning).
Ideal Candidate Profile
- Experienced in building robust data engineering solutions specifically on Azure cloud components and Databricks platform.
- Strong understanding of insurance industry data requirements and governance is preferred to enhance domain-relevant data solutions.
- Demonstrated ability to manage complex data workflows with focus on data quality, compliance, and cross-team collaboration under Agile delivery models.