Senior AWS Data Engineer

Select Minds

  • Dallas, Texas
  • 30+ days ago

    Highlights

    This role requires collaboration across teams to deliver secure, scalable, and high-quality data solutions that drive business intelligence and operational efficiency. Be it understanding your business requirements to choosing the right technologies, we work as a collective team that takes all the possible steps to grow continuously towards our common goal.

    Numbers & Facts

    LocationDallas, Texas
    Websitewww.selectmindsllc.com

    Description

    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, database design, and advanced ETL processes (including Alteryx).
    - Proficiency with structured and semi-structured file types (Delimited Text, Fixed Width, XML, JSON, Parquet).
    - Experience with ServiceBus or equivalent AWS streaming/messaging tools (SNS, SQS, Kinesis, Kafka).
    - CI/CD expertise with GitLab or similar, plus hands-on Infrastructure-as-Code (Terraform, Python, Jinja, YAML).
    - Familiarity with unit testing, code quality tools, containerization, and security best practices.
    - Solid Agile development background, with experience in Agile ceremonies and practices.

    Flexible work from home options available.

    Compensation: $50.00 - $58.00 per hour




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