Overview
On Site
$45-50/hr on w2
Contract - W2
Contract - 12 month(s)
Skills
AWS
ETL
snowflake
Data engineer
Job Details
Job Title: Data Engineer with Snowflake
Location: Mclean,VA (Relocation profiles also workable)
Duration: 12+ months
Contract Type: W2 (No C2C/C2H) only W2 contract
Need strong experience with Snowflake, AWS, SQL, Ab-Initio, Data Architecture, ETL/ELT, Cloud Integration, Data Quality and Performance Optimization. This would be an onsite role at Arlington, VA. Below is the description for reference.
Key Responsibilities:
ETL/ELT Development: Architect and maintain high-performance data pipelines using Ab Initio, handling complex transformations and large data volumes.
Cloud Data Engineering: Build and optimize data platforms on AWS, leveraging services like S3, Lambda, Glue, and IAM for secure, scalable workflows.
Snowflake Expertise: Design efficient schemas, implement clustering strategies, and tune performance for analytics workloads in Snowflake.
Advanced SQL: Develop complex queries, stored procedures, and data validation logic to support reporting, analytics, and downstream systems.
Data Modeling & Governance: Lead efforts in dimensional modeling, metadata management, and data lineage to ensure consistency and compliance.
Performance & Quality: Conduct tuning across ETL jobs and cloud components; implement data quality frameworks to ensure reliability.
Cross-Functional Collaboration: Partner with analysts, data scientists, and business stakeholders to deliver scalable, value-driven solutions.
Mentorship & Leadership: Guide junior engineers, enforce best practices, and contribute to architectural decisions and roadmap planning.
Innovation & Automation: Evaluate new tools, drive automation initiatives, and continuously improve pipeline efficiency and deployment velocity.
Leverage industry best practices and methods.
Define documentation to support the implementation of best practices.
Good communication and stakeholders management.
Key Responsibilities:
ETL/ELT Development: Architect and maintain high-performance data pipelines using Ab Initio, handling complex transformations and large data volumes.
Cloud Data Engineering: Build and optimize data platforms on AWS, leveraging services like S3, Lambda, Glue, and IAM for secure, scalable workflows.
Snowflake Expertise: Design efficient schemas, implement clustering strategies, and tune performance for analytics workloads in Snowflake.
Advanced SQL: Develop complex queries, stored procedures, and data validation logic to support reporting, analytics, and downstream systems.
Data Modeling & Governance: Lead efforts in dimensional modeling, metadata management, and data lineage to ensure consistency and compliance.
Performance & Quality: Conduct tuning across ETL jobs and cloud components; implement data quality frameworks to ensure reliability.
Cross-Functional Collaboration: Partner with analysts, data scientists, and business stakeholders to deliver scalable, value-driven solutions.
Mentorship & Leadership: Guide junior engineers, enforce best practices, and contribute to architectural decisions and roadmap planning.
Innovation & Automation: Evaluate new tools, drive automation initiatives, and continuously improve pipeline efficiency and deployment velocity.
Leverage industry best practices and methods.
Define documentation to support the implementation of best practices.
Good communication and stakeholders management.
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.