4529092-Lead Assistant Manager

Job Title: Senior Data Engineer Job Summary: We are looking for an experienced Senior Data Engineer with 5+ years of hands-on experience in cloud data engineering platforms, specifically AWS, Databricks, and Azure. The ideal candidate will play a critical role in designing, building, and maintaining scalable data pipelines and infrastructure to support our analytics and business intelligence initiatives. Key Responsibilities: Design, develop, and optimize scalable data pipelines using AWS services (e.g., S3, Glue, Redshift, Lambda). Build and maintain ETL/ELT workflows leveraging Databricks and Apache Spark for processing large datasets. Work extensively with Azure data services such as Azure Data Lake, Azure Synapse, Azure Data Factory, and Azure Databricks. Collaborate with data scientists, analysts, and stakeholders to understand data requirements and deliver high-quality data solutions. Ensure data quality, reliability, and security across multiple cloud platforms. Monitor and troubleshoot data pipelines, implement performance tuning, and optimize resource usage. Implement best practices for data governance, metadata management, and documentation. Stay current with emerging cloud data technologies and industry trends to recommend improvements. Required Qualifications: 5+ years of experience in data engineering with strong expertise in AWS , Databricks , and Azure cloud platforms. Hands-on experience with big data processing frameworks, particularly Apache Spark. Proficient in building complex ETL/ELT pipelines and managing data workflows. Strong programming skills in Python, Scala, or Java. Experience working with structured and unstructured data in cloud storage solutions. Knowledge of SQL and experience with relational and NoSQL databases. Familiarity with CI/CD pipelines and DevOps practices in cloud environments. Strong analytical and problem-solving skills with an ability to work independently and in teams. Preferred Skills: Experience with containerization and orchestration tools (Docker, Kubernetes). Familiarity with machine learning pipelines and tools. Knowledge of data modeling, data warehousing, and analytics architecture.EXL is the indispensable partner for leading businesses in data-led industries such as insurance, banking and financial services, healthcare, retail and logistics. We bring a unique combination of data, advanced analytics, digital technology and industry expertise to help our clients turn data into insights, streamline operations, improve customer experience, and transform their business. Our partnerships with clients are built on a foundation of collaboration - and we've been chosen as a partner by nine of the top ten leading US insurance companies, nine of the top 20 global banks, and six of the top ten US health care payers. We function as one team to make your goals our goals, whether that's unlocking the value of generative AI or embedding analytics into workflows that reduce risk or power your growth. Clients choose EXL as their transformation partner for many reasons. Our geographic diversity make talent all over the world instantly accessible. Digital accelerators enable unmatched speed-to-value, letting you realize results fast. It's our people that truly set us apart, though, including the 1,500 data scientists we have dedicated to our generative AI practice. And our more than twenty years of experience in delivering business services, garnering stellar client references, and maintaining a solid balance sheet are reassuring to our C-suite clients. Find out for yourself why clients, employees, and analysts think we're some of the best in the business. Contact us to see how we can help you achieve your goals.