AWS Data Engineer, Databricks & AWS Glue
Overview
You will design, build, and optimize enterprise-scale data platforms on AWS for a Santa Monica-based client. Your work directly impacts data pipelines that process petabytes of information across Databricks and AWS Glue. You will join a team of senior engineers and collaborate with data scientists and analysts. This contract role offers the chance to own high-visibility data initiatives from day one.
What You'll Do7
- 1Design and implement scalable data pipelines using AWS Glue and AWS native services to ingest, transform, and load data from diverse sources.
- 2Develop and maintain Databricks notebooks and jobs for advanced analytics and machine learning workflows.
- 3Build and optimize Spark jobs in Databricks for performance and cost efficiency.
- 4Automate deployment and testing of data pipelines using CI/CD pipelines with tools like Jenkins or GitLab CI.
- 5Collaborate with data architects and engineers to define data models and ensure data quality and integrity.
- 6Troubleshoot and debug production data issues, ensuring high availability and reliability of data platforms.
- 7Drive migration of legacy ETL processes to cloud-native AWS services.
Requirements7
- 110+ years of experience in data engineering, with a focus on cloud data platforms.
- 2Proven expertise with AWS services including S3, EC2, Lambda, Redshift, and Glue.
- 3Hands-on experience with Databricks platform, including notebook development and job orchestration.
- 4Strong proficiency in Python for data processing and scripting.
- 5Experience implementing CI/CD automation for data pipelines using Jenkins, GitLab CI, or AWS CodePipeline.
- 6Experience with Spark and Hive for large-scale data processing.
- 7Domain experience in retail, finance, or healthcare is a plus.
Salary Insight
Salary not disclosed in listing
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