Senior Data Engineer (AWS Hands-On)

New York, NY, US • Posted 12 hours ago • Updated 1 hour ago

Contract W2

On-site

USD $65/hr

Fitment

Dice Job Match Score™

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Job Details

Skills

Data Lake
AWS Glue
Athena

Summary

Job Title: Senior Data Engineer (AWS - Hands-On)

Location: Manhattan, NY (Hybrid - 2 days onsite/week)

Duration: 6 Months (High possibility of extension)

Employment Type: Contract

Billing: 35 hours/week - Only W2 Consultants

Role Overview

We are seeking a highly hands-on Senior Data Engineer to design, build, and maintain scalable data pipelines and analytics platforms within a cloud-native AWS environment.

This role requires deep technical expertise, strong ownership, and the ability to clear rigorous coding interviews. Candidates must demonstrate real-time problem-solving skills and hands-on implementation experience.

MUST HAVE (Strict Screening Criteria)

14+ years overall IT experience
7+ years of strong hands-on Data Engineering experience
Expert-level SQL skills (complex transformations, performance tuning, analytical datasets)
Strong hands-on experience with AWS stack:
- S3 (Data Lake)
- AWS Glue (ETL development using Python)
- Athena (querying & optimization)
- Lambda, Step Functions (orchestration)
- AWS Data Catalog
Hands-on Python development (ETL pipelines - not just scripting)
Proven experience building end-to-end data pipelines (ETL/ELT)
Experience working with large-scale enterprise data systems
Must be able to code live during interviews (no proxy / no support)

Highly Preferred

Experience with Apache Iceberg (Data Lake architecture)
Experience with SnapLogic or similar ETL tools
Exposure to dbt and Snowflake
Experience with BI tools:
- Amazon QuickSight
- Tableau / Power BI
Experience in Banking / Payments / Financial Systems
- ISO 20022, SWIFT, NACHA (plus)
Experience working in regulated environments

Key Responsibilities

Design and develop scalable AWS-based data pipelines
Build and manage enterprise data lake (S3 + Iceberg architecture)
Develop ETL/ELT pipelines using Python & AWS Glue
Create reporting-ready datasets for analytics & BI tools
Implement data quality checks, validation, and monitoring frameworks
Optimize query performance and data processing efficiency
Collaborate with Finance, Technology, and Operations stakeholders
Ensure data governance, lineage, security, and compliance
Troubleshoot production issues and maintain pipeline reliability

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: 10202969
Position Id: PN- 4357-3359-1775501256
Posted 12 hours ago

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