Description
We are looking for an AWS Senior Data Engineer to join a long-term contract opportunity in Southern California. This onsite role requires a highly experienced data engineering specialist who can build resilient, scalable data platforms and support enterprise analytics through well-architected cloud solutions. The ideal candidate will bring deep expertise in AWS-based data ecosystems, modern ETL development, and data warehousing, while maintaining a strong focus on quality, security, and performance.
Responsibilities:
Build and support cloud-based data pipelines that move and transform large volumes of data using AWS services such as S3, Glue, Athena, Redshift, Spectrum, Lambda, and MWAA/Airflow.
Create scalable ETL and ELT workflows with Python, PySpark, Apache Spark, or Scala to deliver reliable datasets for reporting, analytics, and operational use.
Strengthen data quality by implementing validation rules, exception handling, monitoring, and cleansing processes across integration pipelines.
Improve platform efficiency by tuning queries, refining workflow design, and addressing processing bottlenecks to meet performance targets and cost expectations.
Partner with analysts, technical teams, and business stakeholders to convert data needs into technical designs and production-ready engineering solutions.
Maintain dependable data availability for business intelligence initiatives by ensuring pipelines are stable, timely, and aligned with service-level requirements.
Produce and update technical documentation while supporting adherence to data governance, security controls, and regulatory expectations.
Contribute to secure data lake operations through access management, policy enforcement, and governance practices within AWS Lake Formation and related cloud services.
Requirements
At least 7 years of experience in data engineering, database design, ETL development, and data warehousing environments.
Minimum 5 years of hands-on work with AWS data technologies, including S3, Glue, Athena, Redshift, Spectrum, and Airflow or MWAA.
Minimum 5 years of programming experience with Python, PySpark, Scala, or similar technologies used for large-scale data processing.
At least 2 years of experience with CI/CD pipelines and DevOps practices supporting automated deployment and release of data engineering solutions.
Hands-on experience with AWS IAM, AWS Lake Formation, and cloud security concepts such as roles, policies, access controls, and data governance.
Strong understanding of enterprise data storage and processing platforms, including databases, data lakes, and distributed frameworks such as Hadoop or Spark.
Experience working with Informatica PowerCenter or Informatica Cloud in support of integration and data movement initiatives.
Exposure to Agentic AI or Generative AI applications within data engineering is preferred.
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Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: rhalfint
- Position Id: 04837-0013541205
- Posted 2 hours ago
