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Onsite // Data Engineer (ETL, Python, AWS)

  • Source: LinkedIn
  • Talent Groups
  • On-site
  • Iselin
  • Mid level

Job Description

Onsite- (Only W2)

Data Engineer (ETL, Python, AWS)

contract

Iselin, NJ

Job Description:

Overview / Summary

Seeking a professional with strong SQL and ETL architecture expertise to partner with source system owners, business stakeholders, AI engineers, data modelers, and solution architects. The role focuses on gathering data requirements, defining source-to-target mappings, supporting AWS-based data integration solutions, assessing downstream impacts, and ensuring data quality across the data lifecycle.

Key Responsibilities

  • Strong Pyspark Experience is MUST and preference to have Apache Iceberg experience
  • Partner with source system owners and business stakeholders to gather data requirements and translate them into clear, actionable source-to-target mapping documents with documented transformation logic and acceptance criteria.
  • Collaborate directly with AI engineers, data modelers, and solution architects to ensure data pipelines serve both traditional analytics and supports transforming data with high volumes capability.
  • Design and review ETL architecture patterns on AWS (Glue, Step Functions, S3, Redshift/Athena), providing hands-on guidance on job orchestration, partitioning strategies and historic storages.
  • Write detailed JIRA stories covering business value, mapping changes, data onboarding steps, and expected platform impact — stories that engineering teams can pick up with minimum transition support.
  • Assess the impact of new data sources, product changes, or business enhancements on downstream screening and detection platforms, proactively flagging risks before they hit production.
  • Hand off refined requirements to scrum teams and remain partitioning during development and testing.
  • Identify and flag data quality issues at source, working with data stewards and source owners to remediate before data enters the integration layer.
  • Leverage AI-assisted tooling (code generation, automated testing, intelligent data profiling) as a work efficiencies multiplier

Required Qualifications

  • Hands-on SQL experience.
  • Strong ETL architecture knowledge with practical AWS experience (Glue, Lambda, S3, IAM, CloudWatch)
  • Preferred experience on Apache Iceberg

Skills

  • Python
  • amazon-web-services
  • pyspark
  • apache-iceberg
  • aws-glue
  • aws-step-functions
  • amazon-s3
  • amazon-redshift
  • amazon-athena
  • JIRA
  • aws-lambda
  • aws-iam
  • amazon-cloudwatch
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