AWS Senior Data Engineer

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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