AWS Data Engineer

Hybrid in Newark, NJ, US • Posted 7 hours ago • Updated 7 hours ago
Contract Independent
Contract W2
12 Months
No Travel Required
Hybrid
Depends on Experience
Fitment

Dice Job Match Score™

🔢 Crunching numbers...

Job Details

Skills

  • insurance
  • Amazon Web Services
  • Amazon DynamoDB
  • Amazon S3
  • Data Storage
  • Data Processing
  • Data Engineering
  • Data Structure
  • Data Validation

Summary

Job Role: AWS Data Engineer (Insurance domain experience needed)

Location: Newark NJ – (Hybrid/3 days per week) Final interview will happen F2F in Newark, NJ too.

Exp. Start date: Nov 3rd week

Year of Experience: 10+ years

Type: FTE/Contract

 

Role Summary –

Design, develop and support AWS-based data pipelines for enterprise data onboarding, transformation, and consumption. The engineer will work hands-on with Python/PySpark and AWS-native data services to create reliable, scalable, and analytics/AI-ready datasets.

 

Key Responsibilities -

Data Pipeline Development

  • Develop ingestion and transformation pipelines using AWS Glue, EMR, S3, Python and PySpark.
  • Ingest data from legacy and enterprise source systems into AWS.
  • Develop transformations required to create standardized, consumption-ready datasets.
  • Build and maintain ETL/ELT workflows supporting enterprise data domains.

 

AWS Data Engineering

  • Work with S3 for data storage and processing.
  • Develop workloads using Glue and EMR.
  • Develop and optimize analytical datasets and workloads involving Redshift and Athena.
  • Support Iceberg-based data structures on S3 where required.
  • Work with other AWS data services such as DynamoDB when appropriate to the solution.

 

Data Quality & Reliability

  • Implement data validation, reconciliation, and quality checks within pipelines.
  • Identify and resolve data-processing failures and data-quality issues.
  • Support performance optimization of PySpark/SQL workloads and data pipelines.
  • Participate in troubleshooting and production support.

 

Development & Delivery

  • Develop clean, maintainable, and reusable Python/PySpark code.
  • Perform unit and integration testing.
  • Participate in peer code reviews.
  • Document data flows, mappings, transformations, and technical designs.
  • Work with the Data Engineering Lead and client stakeholders to understand source data and transformation requirements.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91133531
  • Position Id: 9138280
  • Posted 7 hours ago
Contact the job poster
PK

Prince Kumar Ravi

Recruiter @ The Hіrеxрrеѕѕ

Create job alert
Never miss an opportunity! Create an alert based on the job you applied for.