Senior AWS Data Engineer (Contract)
Design, develop, and optimize enterprise-scale AWS data pipelines and integrations, focusing on ETL/ELT workflows, data warehousing, and analytics solutions. Requires 5+ years of data engineering experience with deep expertise in AWS Glue, EMR, Redshift, PySpark, and Python. Collaborate with stakeholders to deliver scalable, high-performance data solutions while ensuring cost efficiency and data governance compliance.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
Compensation
Location: Torrance, CA
Pay Range: $70.00 – $77.00 per hour
Schedule: Full-time, Contract
Work Type: 4 days onsite; 1 day remote
📍 Must be willing to work onsite in Torrance, CA
✅ Sponsorship is available for this role
‼️ ONLY W2 – NO CORP TO CORP – NO 3RD PARTIES
Position Summary
We are seeking a Senior AWS Data Engineer to design, develop, optimize, and support enterprise-scale data integration solutions within an AWS cloud environment. This role will focus on building scalable ETL/data pipelines, processing large datasets, maintaining data quality, and delivering reliable data solutions that support business intelligence and analytics.
The ideal candidate has strong hands-on experience with AWS Glue, EMR, MWAA/Airflow, Redshift, PySpark, Apache Spark, Python, and AWS data services, along with a strong understanding of data warehousing, data lakes, distributed computing, and CI/CD.
Key Responsibilities
- Design, develop, and maintain enterprise data integration workflows using AWS Glue, EMR, MWAA/Airflow, Lambda, and Redshift
- Build scalable ETL and ELT pipelines for processing large and complex datasets
- Develop data processing solutions using PySpark, Apache Spark, and Python
- Extract, transform, validate, and load data across enterprise data platforms
- Implement data quality, validation, monitoring, and error-handling mechanisms
- Troubleshoot pipeline failures, data-quality issues, and performance bottlenecks
- Optimize data workflows to improve performance, scalability, reliability, and AWS cost efficiency
- Tune queries and data-processing workloads to improve Amazon Redshift performance
- Develop and maintain data pipelines supporting enterprise analytics and business intelligence
- Translate business requirements into technical specifications and production-ready data solutions
- Collaborate with data analysts, business stakeholders, and technical teams to understand data requirements
- Ensure timely and reliable availability of data for reporting and analytics
- Maintain technical documentation for data pipelines, integrations, workflows, and system specifications
- Support CI/CD processes for data engineering solutions
- Ensure solutions comply with enterprise data governance, security, and regulatory requirements
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What You'll Be Working On
- Enterprise AWS data platforms
- Large-scale ETL and data integration pipelines
- AWS Glue and Amazon EMR
- Apache Spark and PySpark
- Python-based data processing
- Amazon Redshift data warehouses
- Amazon S3 data lakes
- Apache Airflow / Amazon MWAA orchestration
- AWS Lambda
- Amazon Athena, RDS, and Redshift Spectrum
- Data quality and pipeline monitoring
- CI/CD and automated deployments
- Business intelligence and analytics data solutions
- Cloud performance and cost optimization
Required Skills & Experience
- 5+ years of experience in data engineering, database design, ETL processes, and data warehousing
- 3+ years of hands-on AWS data engineering experience
- Strong experience with AWS technologies including:
- Amazon S3
- AWS Glue
- Amazon EMR
- Amazon Athena
- Amazon Redshift
- Amazon RDS
- Redshift Spectrum
- Amazon MWAA / Apache Airflow
- Strong hands-on experience with PySpark and Apache Spark
- 3+ years of programming experience with Python, Java, or Scala
- Strong Python development skills for data engineering and data processing
- Experience designing and supporting scalable ETL/data pipelines
- Strong knowledge of data warehousing and data lake architectures
- Experience working with distributed computing technologies such as Hadoop and Spark
- Experience with data quality, validation, monitoring, and error handling
- Experience troubleshooting and optimizing high-volume data processing workloads
- Experience with SQL and query optimization
- 2+ years of experience with CI/CD tools and processes
- Ability to translate business requirements into technical specifications and data solutions
- Strong analytical, troubleshooting, and problem-solving skills
- Strong communication and cross-functional collaboration skills
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Desired Skills
- Informatica Intelligent Data Management Cloud (IDMC)
- Informatica Cloud
- Agentic AI experience
- Amazon Kiro
- Advanced AWS performance and cost optimization experience
- Experience supporting enterprise business intelligence and analytics environments
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