Senior Data Engineer - PGIM Technology (Hybrid - Newark, NJ)

Prudential Financial

Hybrid

Quick summary

Work type
Hybrid
Location
Newark, NJ
Salary
$115,000–$155,000 / yr
Posted
7 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $178k
This role $135k
$103k most similar roles pay here $227k

This role pays less than 77% of similar roles. Most pay $141,600–$214,462 — the shaded band above. At the midpoint, this role pays about $135k versus about $178k for comparable roles.

Based on 240 similar postings.

Employer

About Prudential Financial

Prudential Financial is a global financial services leader and premier active global investment manager.

Prudential Financial currently has 42 open roles on FindRole.

Listed pay typically runs $133,600–$204,100 across 39 roles with salary data.

Most-posted roles

View all roles at Prudential Financial

At a glance

TL;DR · Senior Data Engineer - PGIM Technology (Hybrid - Newark, NJ)

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As an AI/Data Engineer at Prudential Financial in Newark, NJ, you will join a dynamic team of senior engineers and architects to design and implement scalable data and AI solutions on modern cloud platforms. Your day-to-day responsibilities include building and maintaining ETL/ELT pipelines, developing semantic search and Retrieval-Augmented Generation (RAG) capabilities, and deploying machine learning models into production systems. You will work with large-scale datasets using PySpark and SQL, contribute to CI/CD pipelines, and ensure data security and governance best practices are followed. The role requires strong Python and SQL skills, experience with Azure Data Factory or similar tools, familiarity with data lakes and warehouses, and exposure to generative AI technologies such as embeddings and LLM APIs.

Skills

Python SQL Azure Data Factory Microsoft Fabric PySpark GitHub Actions Azure DevOps MLOps REST APIs CI/CD Git Data Security Data Governance AWS Glue

What you'll do

  • Design and maintain scalable data pipelines using ETL/ELT processes.
  • Develop AI-powered solutions like semantic search and Retrieval-Augmented Generation (RAG).
  • Implement data quality checks and transformations for large-scale datasets.
  • Deploy machine learning models into production environments seamlessly.
  • Build and expose data and AI services via REST APIs for integration.

What we're looking for

  • 3-6 years of data/AI engineering experience
  • Strong Python and SQL proficiency
  • Experience with data pipeline tools like ADF or AWS Glue
  • Proficiency in Spark/PySpark for large-scale datasets
  • Knowledge of deploying machine learning models
  • Familiarity with generative AI technologies (embeddings, RAG)
  • Understanding of REST APIs and microservices

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