AWS Data Engineer

Senior AWS Data Engineer (Glue, PySpark, Redshift) • Job Title: Senior AWS Data Engineer (Glue, PySpark, Redshift) • Location: Newark NJ • Client: CTS/PSEG Job Summary We are seeking a highly skilled Senior AWS Data Engineer responsible for designing, developing, and deploying robust ELT/ETL pipelines within the AWS environment. The core focus is on end-to-end data integration from diverse enterprise sources (SAP, Salesforce, OKTA) through AWS S3 into Redshift for analytical use. The candidate must be proficient in using AWS Glue, Step Functions, and Lambda and possess strong automation skills using Python/PySpark and Redshift SQL. Expertise in implementing CI/CD deployment via GitHub and adhering to PSEG governance standards is required. Key Focus Areas & Required Technical Skills • Pipeline Development: Develop and maintain ELT/ETL pipelines using AWS Glue, Step Functions, Lambda, DMS, and AppFlow. • Programming & Automation: Automate transformations and model refresh using Python, PySpark, and SQL. • Data Flow: Implement end-to-end source-to-target data integration across the entire data lake architecture: Data Source AWS S3 Raw Curated Redshift. • Data Warehousing: Proficient in Redshift SQL for transformations, optimization, and model refresh. • Source Integration: Experience integrating with on-prem and SaaS data sources, such as SAP (via Simplement), Salesforce, OKTA, MuleSoft, and JAMS. • DevOps & Governance: Implement CI/CD deployment using GitHub and deploy code following PSEG governance and change control processes. • Metadata & Security: Manage metadata and lineage via AWS Glue Data Catalog. Familiarity with CloudWatch, CloudTrail, and Secrets Manager for monitoring and security. Preferred Certifications • AWS Certified Data Engineer – Associate • AWS Certified Developer – Associate