8 days ago
Base Salary
$150k - $170k/yr
Responsibilities
- Design, build, and maintain scalable data pipeline architectures and data applications on AWS.
- Develop ingestion, ETL/ELT, data lake, data warehouse, and data migration solutions.
- Implement serverless applications and high-velocity streaming solutions using AWS services and Kafka.
- Architect end-to-end data solutions spanning ingestion, storage, processing, integration, and access.
- Participate in system architecture and design discussions for high-scale data engineering projects.
- Perform hands-on development, unit testing, code reviews, and data quality and security improvements.
- Architect CI/CD strategies for enterprise data platforms.
- Identify and resolve performance issues while optimizing cost, reliability, and scalability.
- Collaborate with product, operations, QA, data scientists, analysts, and other cross-functional stakeholders.
- Evaluate new technologies, develop proofs of concept, and onboard tools for production use.
- Oversee organizational data engineering solutions, lead high-impact initiatives, and provide executive guidance.
Requirements
- Bachelor’s degree in Computer Science, Software Engineering, MIS, or an equivalent combination of education and experience.
- 8+ years of experience implementing and supporting AWS data lakes, data warehouses, and data applications for large enterprises.
- Strong programming experience with Python, Shell scripting, and SQL.
- Experience with AWS services including CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, and Secrets Manager.
- Experience with serverless application development, data pipeline orchestration, system analysis, design, development, and implementation.
- Knowledge of ETL/ELT, data modeling, big data technologies, data warehousing, and cloud-based architecture.
- Strong problem-solving, attention to detail, communication, and teamwork abilities.
- Preferred experience with API Gateway, Elasticsearch, and SQS.
- Preferred experience with Terraform, DevOps practices, CI/CD pipelines, streaming solutions, Kafka, lakehouse or data cloud architecture, and data governance and compliance standards.
- AWS Solutions Architect or AWS Developer Certification is preferred.
- The qualifications section also states graduate-level education in Computer Science, Data Science, or a related field and 6–8 years of experience in data engineering or a related field.
Tech Stack
Categories
Data Engineering
About EXL
EXL provides data analytics, AI, and digital operations services for enterprises in insurance, healthcare, banking, and other regulated industries. It delivers consulting, managed services, and technology platforms to improve decision-making, risk management, and operational efficiency. Founded in 1999 and headquartered in New York, EXL is a public company listed on the NASDAQ (ticker: EXLS).