Senior AWS Data Engineer

About this role

Benefits:

• HYBRID
• Competitive salary
• Opportunity for advancement

Job Title: Data Quality Engineer
Location: Dallas, TX (Hybrid – 3 days onsite)
Job Type: Long-term Contract
Work Authorization: Open - W2 opportunity
Profiles : 5-10yrs
Interview Process: In-person (Client interview- Mandatory)

Overview
We are looking for an experienced AWS Data Engineer with strong expertise in ETL, cloud migration, and large-scale data engineering. The ideal candidate is hands-on with AWS, Python/PySpark, and SQL, and can design, optimize, and manage complex data pipelines. This role requires collaboration across teams to deliver secure, scalable, and high-quality data solutions that drive business intelligence and operational efficiency.

Key Responsibilities

• Design, build, and maintain scalable ETL pipelines across AWS and SQL-based technologies.
• Assemble large, complex datasets that meet business and technical requirements.
• Implement process improvements by re-architecting infrastructure, optimizing data delivery, and automating workflows.
• Ensure data quality and integrity across multiple sources and targets.
• Orchestrate workflows with Apache Airflow (MWAA) and support large-scale cloud migration projects.
• Conduct ETL testing, apply test-driven development (TDD), and participate in code reviews.
• Monitor, troubleshoot, and optimize pipelines for performance, reliability, and security.
• Collaborate with cross-functional teams and participate in Agile ceremonies (sprints, reviews, stand-ups).

Requirements

• 5–10 years of experience in Data Engineering, with deep focus on ETL, cloud pipelines, and Python development.
• 3+ years of hands-on coding with Python (primary), PySpark, and SQL.
• Proven experience with AWS services: Glue, EMR (Spark), S3, Lambda, ECS/EKS, MWAA (Airflow), IAM.
• Experience with AuroraDB,DynamoDB Redshift, and AWS Data Lakes.
• Strong knowledge of data modeling, databas...