Talent Groups
Onsite // Data Engineer (ETL, Python, AWS)
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Onsite Data Engineer (ETL, Python, AWS) in Iselin, NJ, on a contract basis. Required skills include strong SQL, ETL architecture, AWS experience, and Pyspark expertise. Preferred experience with Apache Iceberg.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
July 15, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Iselin, NJ
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🧠 - Skills detailed
#"ETL (Extract #Transform #Load)" #Storage #Data Profiling #S3 (Amazon Simple Storage Service) #SQL (Structured Query Language) #Data Engineering #Data Integration #PySpark #Redshift #Spark (Apache Spark) #Data Quality #IAM (Identity and Access Management) #Data Lifecycle #Apache Iceberg #Data Pipeline #Python #AWS (Amazon Web Services) #Lambda (AWS Lambda) #Stories #Scrum #AI (Artificial Intelligence) #Jira #Cloud #AWS Glue #Athena #Automated Testing
Role 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
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
