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AWS Data Engineer

Prudent Technologies and ConsultingNew York, NY🇺🇸United StatesPosted 18 Aug 2026

Why This Role Stands Out

This hybrid AWS Data Engineer role offers a fantastic opportunity to leverage your expertise in Snowflake, Python, and Airflow to build scalable data solutions within a reputable consulting firm. You'll thrive here if you enjoy collaborating with diverse teams and contributing to impactful data products, with ample room for continued professional growth. Apply today to join their innovative environment and advance your career in data engineering.

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Role: Data Engineer

Location: 3 days’ work from NYC, NY

Employment Type: Full-time position

 

Skillset: Snowflake, complex SQL queries, performance tuning, Python, Airflow, Data Modelling & proficiency in using AI

 

Key Responsibilities:

  • Develop and maintain data platform pipelines and data integration processes.
  • Support the implementation of conceptual, logical, and physical data models.
  • Build and maintain data transformations using dbt and contribute to scalable, reliable data solutions.
  • Collaborate with data engineers, data scientists, analysts, and cross-functional teams to deliver data products.
  • Apply data engineering concepts and technologies, including AWS services (S3, Lambda, SNS, SQS), Iceberg, Snowflake, dbt, and Airflow.
  • Participate in Agile/Scrum ceremonies and contribute to team planning and continuous improvement efforts.
  • Work with product managers, architects, and engineers to support the Core Data Platform roadmap.
  • Follow established standards and best practices for data pipelines, naming conventions, and platform development.
  • Monitor and support the quality, reliability, and operational health of data platform datasets and pipelines.
  • Contribute to documentation of data assets, processes, and platform standards.
  • Partner with stakeholders to understand business requirements and support delivery of data solutions.
  • Maintain documentation to support data quality, governance, and operational requirements.

 

Qualifications:

  • 7+ years of experience developing and supporting data pipelines.
  • Understanding of data modeling concepts, including dimensional modeling and data normalization principles.
  • Proficiency in at least one program

Skills

SQL
AWS
Scrum
Snowflake
Agile
Airflow
Python
dbt

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