Senior Data Engineer - PGIM Technology

Benefits

Location: Newark, NJ with a hybrid work arrangement. Salary: USD 115,000 - 155,000 per year, plus a yearly bonus potential. Prudential offers a comprehensive benefits package designed to support your health, wealth, and work-life balance.

• Medical, dental, vision, life insurance, and disability coverage
• PTO and leave options including parental and military leave
• 401(k) with company match up to 4%
• Company-funded pension plan
• Wellness programs including up to $1,600 per year for personal wellbeing purchases
• Work/Life Resources to support parenting, housing, senior care, finances, pets, legal matters, education, emotional and mental health, and career development
• Educational benefits to finance traditional college enrollment or accredited certificate programs
• Employee Stock Purchase Plan with purchase at 85% of the lower price after one year of service

Responsibilities

• Build and maintain scalable data pipelines (ETL/ELT)
• Develop solutions using Microsoft Fabric, Azure Data Factory, or similar
• Implement data quality checks, transformations, and data modeling
• Work with large-scale datasets using PySpark / SQL
• Deploy and integrate machine learning models into pipelines
• Develop AI-powered solutions (semantic search, embeddings, RAG)
• Build and expose data and AI services via APIs
• Contribute to CI/CD pipelines using GitHub Actions or Azure DevOps
• Implement best practices for data security, governance, and access
• Monitor and troubleshoot pipelines and AI systems
• Collaborate with analysts, scientists, and stakeholders
• Contribute to documentation and reusable components

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field
• 3–6 years of experience in data/AI engineering
• Strong Python and SQL skills
• Experience with data pipeline tools (ADF, Fabric, AWS Glue, etc.)
• Experience with Spark/PySpark
• Familiarity with data lakes and warehouses
• Experience deploying ML models
• Basic MLOps understanding
• Exposure to Generative AI (embeddings, RAG, LLM APIs)
• Experience with REST APIs and microservices
• Familiarity with CI/CD and Git
• Understanding of data governance and security
• Strong problem-solving and communication skills

Technologies

• Python
• SQL
• PySpark
• Spark
• Microsoft Fabric
• Azure Data Factory
• AWS Glue
• GitHub Actions
• Azure DevOps
• REST APIs