Senior Data Engineer

Job Description

Role Overview:

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• 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
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• They will be part of an agile team that combines various backgrounds, experiences, and perspectives to solve complex problems within AWS and beyond.
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• The person will also be required to participate actively in brainstorming sessions for improvement opportunities and take it to completion
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• 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.
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• Experience in life insurance preferred but not mandatory.
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Key Responsibilities & Skillsets:

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• Common Skillsets:
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• Superior analytical and problem solving skills
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• Should be able to work on a problem independently and prepare client ready deliverable with minimal or no supervision
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• Good communication skill for client interaction
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Application development Skillsets:

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• Strong ability to debug complex data workflows, optimize application and ETL code, and automate data transformation processes
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• Systematic, analytical problem‑solving approach with strong ownership over data quality, performance, and delivery
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• Ability to quickly evaluate new AWS data and analytics services and determine fit for data pipelines or application architecture
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• Hands‑on experience developing data workflows and infrastructure using IaC frameworks such as CloudFormation or Terraform (as needed)
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• Working knowledge of CI/CD pipelines primarily to support data application deployments (Jenkins, CodePipeline, etc.)
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• Proficient with Git for versioning data processing code, libraries, and application components
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• Skilled in writing production‑grade code in Python, Node.js, Bash, PowerShell, or similar languages, focusing on data processing and backend development
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• Experience using Docker for packaging applications and data-processing workloads, with exposure to containerized data services (ECS, EKS, etc.)
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• Comfortable developing and troubleshooting in Linux environments
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• Solid understanding of key AWS data services and application primitives such as S3, EC2, Glue, EMR, Lambda, RDS, DynamoDB, CloudWatch, and VPC networking concepts
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• Strong knowledge of AWS security and IAM as it relates to data pipelines, encryption (KMS), secure data access (IAM roles/policies), and audit controls
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• Hands‑on experience with ETL, distributed compute, and big data frameworks such as Spark, Glue, Hadoop/EMR, Impala, or similar tooling
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• Deep understanding of relational databases, SQL optimization, and application‑to‑database interaction patterns
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• Familiarity with log analytics and observability platforms (Splunk, ELK, Prometheus, Grafana) as they relate to monitoring data pipelines and applications
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Candidate Profile:

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• Bachelor’s/Master's degree in computer science/engineering, operations research or related analytics areas welcome to apply
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• 8+ years’ experience in AWS Data Engineering, preferably in Life Insurance but not mandatory
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• Application development experience
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• Team Management
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• Superior analytical and problem solving skills
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• Outstanding written and verbal communication skills
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• Able to work in fast pace continuously evolving environment and ready to take up uphill challenges
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• Can understand cross cultural differences and can work with clients across the globe
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