AWS Data Engineer

The person will be part of the Global Technology team for a major Insurance client. He/ She will work as a Senior Cloud Engineer within the CDO EDP team and will have the opportunity to work one-on-one with application and infrastructure developers to build and enhance the data infrastructure and application patterns that power mission-critical applications, ensuring that they’re engineered for high availability, durability, and resiliency They will be part of an agile team that combines various backgrounds, experiences, and perspectives to solve complex problems within AWS and beyond. The person will also be required to participate actively in brainstorming sessions for improvement opportunities and take it to completion A suitable candidate should have 8+ years of IT experience with at least 5+ years of experience working as an AWS Data Engineer. He/ She should be able to deal with ambiguity. Experience in life insurance preferred but not mandatory. Key Responsibilities & Skillsets: Superior analytical and problem solving skills Should be able to work on a problem independently and prepare client ready deliverable with minimal or no supervision Good communication skill for client interaction Strong ability to debug complex data workflows, optimize application and ETL code, and automate data transformation processes Systematic, analytical problem-solving approach with strong ownership over data quality, performance, and delivery Ability to quickly evaluate new AWS data and analytics services and determine fit for data pipelines or application architecture Hands-on experience developing data workflows and infrastructure using IaC frameworks such as CloudFormation or Terraform (as needed) Working knowledge of CI/CD pipelines primarily to support data application deployments (Jenkins, CodePipeline, etc.) Proficient with Git for versioning data processing code, libraries, and application components Skilled in writing production-grade code in Python, Node.js, Bash, PowerShell, or similar languages, focusing on data processing and backend development Experience using Docker for packaging applications and data-processing workloads, with exposure to containerized data services (ECS, EKS, etc.) Comfortable developing and troubleshooting in Linux environments Solid understanding of key AWS data services and application primitives such as S3, EC2, Glue, EMR, Lambda, RDS, DynamoDB, CloudWatch, and VPC networking concepts Strong knowledge of AWS security and IAM as it relates to data pipelines, encryption (KMS), secure data access (IAM roles/policies), and audit controls Hands-on experience with ETL, distributed compute, and big data frameworks such as Spark, Glue, Hadoop/EMR, Impala, or similar tooling Deep understanding of relational databases, SQL optimization, and application-to-database interaction patterns Familiarity with log analytics and observability platforms (Splunk, ELK, Prometheus, Grafana) as they relate to monitoring data pipelines and applications Candidate Profile: Bachelor’s/Master's degree in computer science/engineering, operations research or related analytics areas welcome to apply 8+ years’ experience in AWS Data Engineering, preferably in Life Insurance but not mandatory Team Management Superior analytical and problem solving skills Outstanding written and verbal communication skills Able to work in fast pace continuously evolving environment and ready to take up uphill challenges Can understand cross cultural differences and can work with clients across the globe Preferably based out of the New Jersey area with at least three days of work from office at the client’s location in Newark, NJ #J-18808-Ljbffr