Senior AWS Data Engineer

🕒 July 4

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EXL

WebsiteLinkedInAll Job Openings

10,000+ employees

🏥 Healthcare

🛡️ Insurance

📦 Logistics

💰 $2M Venture Round on 2015-01

Healthcare • Insurance • Logistics

EXL is a business consulting and services firm that focuses on leveraging data to enhance business operations and decision-making. With a strong emphasis on collaboration and adaptability, EXL partners with organizations to address their unique needs and culture while integrating data science and technology solutions. The company's areas of expertise include operations management, decision analytics, digital transformation, and various industries such as healthcare, finance, and insurance. EXL's mission is to help clients drive business evolution and maintain competitive advantage through tailored solutions and effective use of data.

📋 Description

• Manage data engineering projects, ensuring alignment with business objectives. • Provide strategic guidance on data engineering best practices. • Oversee a team of data engineers. • Ensure continuous improvement of data processes. • Design, build, and maintain efficient, reusable, and reliable architecture and code for data pipelines and data applications on AWS. • Build robust data ingestion pipelines (from on-prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS. • Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security. • Architect and implement end-to-end data solutions (ingestion, storage, integration, processing, access) on AWS, with a focus on data lakes and data warehouses. • Participate in the architecture and system design discussions for high-scale data engineering projects. • Independently perform hands-on development, unit testing, and participate in code reviews to ensure adherence to best practices. • Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS technologies. • Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift. • Implement high-velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred). • Architect and implement CI/CD strategies for enterprise data platforms. • Collaborate with product, operations, QA, and cross-functional teams throughout the software development cycle. • Stay abreast of new technology developments, implement POCs for new tools/technologies, and onboard them for real-world use cases. • Identify and resolve performance issues and continuously optimize for cost, reliability, and scalability.

🎯 Requirements

• Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience. • 5+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises. • Strong programming experience with Python, Shell scripting, and SQL. • Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager. • Experience in serverless application development and data pipeline orchestration. • Experience in system analysis, design, development, and implementation of data ingestion pipelines in AWS. • Knowledge of ETL/ELT, data modeling, and big data technologies. • Familiarity with data warehousing concepts and cloud-based architecture. • Strong problem-solving skills and attention to detail. • Excellent communication and teamwork abilities.

🏖️ Benefits

• Work From Home