Databricks Developer
EXL
Databricks Developer
EXL
Analyzes business data and runs outsourced operations
Role: Data Bricks Developer
Experience: 5+ Years
Location: Gurgaon OR Bangalore
Work Mode: Work From Office [5 Days Office]
POSITION SUMMARY
The Databricks Data Engineer will be responsible for designing, building, and optimizing scalable data pipelines and lakehouse solutions using Databricks. The role requires strong hands-on experience in data engineering, distributed data processing.
ROLES AND RESPONSIBILITIES:
• Design, build, and maintain ETL/ELT pipelines on Databricks using PySpark, Spark SQL, and Delta Lake.
• Develop and optimize data ingestion frameworks, data transformations, and end to end workflows for batch and streaming use cases.
• Implement Delta Lake based architectures, including versioning, schema evolution, and ACID compliant pipelines.
• Work with stakeholders to understand data requirements and translate them into scalable data engineering solutions.
• Manage and optimize Databricks clusters, jobs, and notebooks for performance and cost efficiency.
• Ensure data quality, reliability, and observability through validation frameworks and monitoring.
• Contribute to data modeling, metadata management, and best practices within the data platform. REQUIRED QUALIFICATIONS
• 3+ years of experience in data engineering with 2+ years of hands on expertise in Databricks.
• Hands on experience with Spark (PySpark/Spark SQL) and distributed data processing.
• Solid SQL knowledge and experience working with large-scale datasets
• Strong understanding of Delta Lake, medallion architecture, and scalable lakehouse patterns.
• Good understanding of CI/CD, Git, and modern DevOps practices for data pipelines.
• Familiarity with structured/unstructured data, data quality frameworks, and performance tuning.
EDUCATION: Bachelor’s degree in computer science, Software Engineering, MIS or equivalent combination of education and experience
KEY SKILLS: Data Engineering, Python, Pyspark, Azure Cloud, Azure Data Bricks
Bachelor’s degree in computer science, Software Engineering, MIS or equivalent combination of education and experience
• Design, build, and maintain ETL/ELT pipelines on Databricks using PySpark, Spark SQL, and Delta Lake.
• Develop and optimize data ingestion frameworks, data transformations, and end to end workflows for batch and streaming use cases.
• Implement Delta Lake based architectures, including versioning, schema evolution, and ACID compliant pipelines.
• Work with stakeholders to understand data requirements and translate them into scalable data engineering solutions.
• Manage and optimize Databricks clusters, jobs, and notebooks for performance and cost efficiency.
• Ensure data quality, reliability, and observability through validation frameworks and monitoring.
• Contribute to data modeling, metadata management, and best practices within the data platform. REQUIRED QUALIFICATIONS
• 3+ years of experience in data engineering with 2+ years of hands on expertise in Databricks.
• Hands on experience with Spark (PySpark/Spark SQL) and distributed data processing.
• Solid SQL knowledge and experience working with large-scale datasets
• Strong understanding of Delta Lake, medallion architecture, and scalable lakehouse patterns.
• Good understanding of CI/CD, Git, and modern DevOps practices for data pipelines.
• Familiarity with structured/unstructured data, data quality frameworks, and performance tuning.
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.
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