About this role
EXL (NASDAQ: EXLS) is a leading data analytics and digital operations and solutions company. We partner with clients using a data and AI-led approach to reinvent business models, drive better business outcomes and unlock growth with speed. EXL harnesses the power of data, analytics, AI, and deep industry knowledge to transform operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media and retail, among others. EXL was founded in 1999 with the core values of innovation, collaboration, excellence, integrity and respect. We are headquartered in New York and have more than 54,000 employees spanning six continents. For more information, visit www.exlservice.com.
EXL never requires or asks for fees/payments or credit card or bank details during any phase of the recruitment or hiring process and has not authorized any agencies or partners to collect any fee or payment from prospective candidates. EXL will only extend a job offer after a candidate has gone through a formal interview process with members of EXL’s Human Resources team, as well as our hiring managers.
Job Description: Azure / Databricks Data Engineer (9-15 Years Experience) Job Title
Senior Azure Databricks Data Engineer
Experience
9-15 Years of IT Experience
Location
Hybrid
Job Summary
We are seeking a skilled Databricks Engineer with minimum of 5+ years of hands-on in Databricks who can design, develop, and optimize scalable data platforms and analytics solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in data engineering, ETL/ELT development, cloud technologies preferably Azure, and big data processing to support enterprise analytics and AI initiatives.
Key Responsibilities
• Design, develop, and maintain data pipelines using Databricks, Apache Spark, and cloud-native services. • Build and optimize ETL/ELT workflows for large-scale structured and unstructured data. • Develop data models and implement data quality, validation, and governance frameworks. • Integrate data from multiple sources into a unified Lakehouse architecture. • Optimize Spark jobs and Databricks workloads for performance, scalability, and cost efficiency. • Implement security controls, access management, and data governance using Unity Catalog. • Collaborate with business, analytics, and AI/ML teams to deliver trusted data products. • Monitor, troubleshoot, and resolve data pipeline issues. • Support CI/CD, DevOps, and infrastructure automation practices. • Maintain technical documentation and best practices.
Required Technical Skills Core Technologies
• Databricks Lakehouse Platform • Apache Spark / PySpark • Delta Lake • SQL • Python
Data Engineering
• ETL / ELT Development • Data Modeling • Data Warehousing • Data Quality & Validation • Streaming & Real-Time Processing
Governance & Security
• Unity Catalog • Data Lineage • Row-Level Security • Access Control & Compliance • Data Governance Frameworks
Cloud & DevOps
• Azure / AWS / GCP • Terraform • GitHub Actions / Azure DevOps • CI/CD Pipelines
Analytics & AI
• Semantic Layers • Data Products • BI Platforms • Machine Learning Support • Generative AI & RAG Architectures
Required Qualifications
• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field. • 9-15 years of experience in Data Engineering and Data Warehousing. • Minimum 5+ years of hands-on experience with Azure Data Engineering technologies. • Minimum 4+ years of hands-on experience with Azure Databricks and Spark ecosystem. • Strong understanding of data lake, lakehouse, and cloud-native architecture patterns. • Experience in handling large-scale structured and unstructured datasets. • Strong analytical, problem-solving, and troubleshooting skills.
Preferred Qualifications
• Microsoft Certified: Azure Data Engineer Associate (DP-203). • Databricks Certified Data Engineer Associate/Professional. • Experience with Snowflake, Power BI, or Microsoft Fabric. • Experience in real-time streaming solutions using Kafka/Event Hubs. • Exposure to Data Governance and Master Data Management initiatives.
Soft Skills
• Strong stakeholder management and communication skills. • Ability to lead technical initiatives and drive architecture discussions. • Experience working in Agile/Scrum environments. • Excellent documentation and presentation skills. • Strong mentoring and team leadership abilities.
Nice to Have
• Microsoft Fabric • Power BI • Azure Event Hubs • Kafka • Machine Learning data pipelines • Data Governance tools such as Purview
Job Description: Azure / Databricks Data Engineer (9-15 Years Experience) Job Title
Senior Azure Databricks Data Engineer
Experience
9-15 Years of IT Experience
Location
Hybrid
Job Summary
We are seeking a skilled Databricks Engineer with minimum of 5+ years of hands-on in Databricks who can design, develop, and optimize scalable data platforms and analytics solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in data engineering, ETL/ELT development, cloud technologies preferably Azure, and big data processing to support enterprise analytics and AI initiatives.
Key Responsibilities
• Design, develop, and maintain data pipelines using Databricks, Apache Spark, and cloud-native services. • Build and optimize ETL/ELT workflows for large-scale structured and unstructured data. • Develop data models and implement data quality, validation, and governance frameworks. • Integrate data from multiple sources into a unified Lakehouse architecture. • Optimize Spark jobs and Databricks workloads for performance, scalability, and cost efficiency. • Implement security controls, access management, and data governance using Unity Catalog. • Collaborate with business, analytics, and AI/ML teams to deliver trusted data products. • Monitor, troubleshoot, and resolve data pipeline issues. • Support CI/CD, DevOps, and infrastructure automation practices. • Maintain technical documentation and best practices.
Required Technical Skills Core Technologies
• Databricks Lakehouse Platform • Apache Spark / PySpark • Delta Lake • SQL • Python
Data Engineering
• ETL / ELT Development • Data Modeling • Data Warehousing • Data Quality & Validation • Streaming & Real-Time Processing
Governance & Security
• Unity Catalog • Data Lineage • Row-Level Security • Access Control & Compliance • Data Governance Frameworks
Cloud & DevOps
• Azure / AWS / GCP • Terraform • GitHub Actions / Azure DevOps • CI/CD Pipelines
Analytics & AI
• Semantic Layers • Data Products • BI Platforms • Machine Learning Support • Generative AI & RAG Architectures
Required Qualifications
• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field. • 9-15 years of experience in Data Engineering and Data Warehousing. • Minimum 5+ years of hands-on experience with Azure Data Engineering technologies. • Minimum 4+ years of hands-on experience with Azure Databricks and Spark ecosystem. • Strong understanding of data lake, lakehouse, and cloud-native architecture patterns. • Experience in handling large-scale structured and unstructured datasets. • Strong analytical, problem-solving, and troubleshooting skills.
Preferred Qualifications
• Microsoft Certified: Azure Data Engineer Associate (DP-203). • Databricks Certified Data Engineer Associate/Professional. • Experience with Snowflake, Power BI, or Microsoft Fabric. • Experience in real-time streaming solutions using Kafka/Event Hubs. • Exposure to Data Governance and Master Data Management initiatives.
Soft Skills
• Strong stakeholder management and communication skills. • Ability to lead technical initiatives and drive architecture discussions. • Experience working in Agile/Scrum environments. • Excellent documentation and presentation skills. • Strong mentoring and team leadership abilities.
Nice to Have
• Microsoft Fabric • Power BI • Azure Event Hubs • Kafka • Machine Learning data pipelines • Data Governance tools such as Purview
Job Description: Azure / Databricks Data Engineer (9-15 Years Experience) Job Title
Senior Azure Databricks Data Engineer
Experience
9-15 Years of IT Experience
Location
Hybrid
Job Summary
We are seeking a skilled Databricks Engineer with minimum of 5+ years of hands-on in Databricks who can design, develop, and optimize scalable data platforms and analytics solutions using the Databricks Lakehouse Platform. The ideal candidate will have expertise in data engineering, ETL/ELT development, cloud technologies preferably Azure, and big data processing to support enterprise analytics and AI initiatives.
Key Responsibilities
• Design, develop, and maintain data pipelines using Databricks, Apache Spark, and cloud-native services. • Build and optimize ETL/ELT workflows for large-scale structured and unstructured data. • Develop data models and implement data quality, validation, and governance frameworks. • Integrate data from multiple sources into a unified Lakehouse architecture. • Optimize Spark jobs and Databricks workloads for performance, scalability, and cost efficiency. • Implement security controls, access management, and data governance using Unity Catalog. • Collaborate with business, analytics, and AI/ML teams to deliver trusted data products. • Monitor, troubleshoot, and resolve data pipeline issues. • Support CI/CD, DevOps, and infrastructure automation practices. • Maintain technical documentation and best practices.
Required Technical Skills Core Technologies
• Databricks Lakehouse Platform • Apache Spark / PySpark • Delta Lake • SQL • Python
Data Engineering
• ETL / ELT Development • Data Modeling • Data Warehousing • Data Quality & Validation • Streaming & Real-Time Processing
Governance & Security
• Unity Catalog • Data Lineage • Row-Level Security • Access Control & Compliance • Data Governance Frameworks
Cloud & DevOps
• Azure / AWS / GCP • Terraform • GitHub Actions / Azure DevOps • CI/CD Pipelines
Analytics & AI
• Semantic Layers • Data Products • BI Platforms • Machine Learning Support • Generative AI & RAG Architectures
Required Qualifications
• Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or related field. • 9-15 years of experience in Data Engineering and Data Warehousing. • Minimum 5+ years of hands-on experience with Azure Data Engineering technologies. • Minimum 4+ years of hands-on experience with Azure Databricks and Spark ecosystem. • Strong understanding of data lake, lakehouse, and cloud-native architecture patterns. • Experience in handling large-scale structured and unstructured datasets. • Strong analytical, problem-solving, and troubleshooting skills.
Preferred Qualifications
• Microsoft Certified: Azure Data Engineer Associate (DP-203). • Databricks Certified Data Engineer Associate/Professional. • Experience with Snowflake, Power BI, or Microsoft Fabric. • Experience in real-time streaming solutions using Kafka/Event Hubs. • Exposure to Data Governance and Master Data Management initiatives.
Soft Skills
• Strong stakeholder management and communication skills. • Ability to lead technical initiatives and drive architecture discussions. • Experience working in Agile/Scrum environments. • Excellent documentation and presentation skills. • Strong mentoring and team leadership abilities.
Nice to Have
• Microsoft Fabric • Power BI • Azure Event Hubs • Kafka • Machine Learning data pipelines • Data Governance tools such as Purview