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Senior AWS Data Engineer

  • Dallas, TX, United States

$50 to $58 USD / hour

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Job details

Pay
$50 to $58 USD / hour
Experience
5–10 years of experience in Data Engineering, with deep focus on ETL, cloud pipelines, and Python development.
Posting language
English
Posted

Original job 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.

More about this job

Skills

  • AWS
  • Data engineering
  • Python
  • PySpark
  • SQL
  • Apache Airflow
  • EMR
  • Apache Spark
  • Identity and access management
  • Amazon DynamoDB
  • Amazon Redshift
  • Data modelling
  • Alteryx
  • Apache Kafka
  • CI/CD
  • GitLab
  • Infrastructure as code
  • IBM Terraform
  • Unit testing
  • Agile development
  • Agile

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