Senior AWS Data Engineer

Select Minds LLC
Dallas, United States of America
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Remote
Dallas, United States of America

Tech stack

Agile Methodologies
Airflow
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Unit Testing
Big Data
Software Quality
Code Review
Continuous Integration
Information Engineering
ETL
Data Systems
Database Design
Amazon DynamoDB
Identity and Access Management
JSON
Jinja (Template Engine)
Python
Amazon Web Services (AWS)
SQL Databases
XML
YAML
Parquet
Test Driven Development
Spark
Gitlab
Servicebus
Containerization
PySpark
Amazon Web Services (AWS)
Kafka
Cloud Migration
Data Delivery
Software Coding
Amazon Web Services (AWS)
Terraform
Data Pipelines
Alteryx

Job description

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.

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