Senior Data Engineer – Financial Data Lakes & Pipelines

PGIM Ireland; The Ironbound (NJ); On-site; USD 104,000 - 172,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) plan with company match

Pension plan

Wellness programs

Job summary

PGIM is seeking a Senior Data Engineer for the FM Management Reporting team to build and optimize data pipelines, data lakes and analytics-ready datasets. You will collaborate with architects, data scientists and analysts to deliver high-quality code and scalable solutions.

The role involves applying modern tools like Spark, SQL, Python, and AWS services, with emphasis on data reliability, processing, and governance in a financial services context.

Qualifications

• Bachelor of Computer Science or Engineering or related field.
• Experience with DevOps automation and SDLC.
• Ability to learn new skills continuously and work in teams.
• Strong problem solving and communication skills.

Responsibilities

• Build and optimize data pipelines, logic and storage systems.
• Develop high quality, well documented code meeting standards.
• Analyze data for prescriptive and predictive modeling.
• Collaborate with analysts, scientists and architects on data projects.
• Write tests and automate quality assurance.
• Apply emerging technologies and coach others when appropriate.
• Work on complex problems requiring deep evaluation.

Skills

Python

SQL

Spark

Pyspark

Airflow

AWS

Data Lakes

Big Data

DevOps

Problem Solving

Education

Bachelor of Computer Science or Engineering

Tools

AWS

Snowflake

Redshift

Tableau

Power BI

Kinesis

Kafka

Airflow

CloudFormation

Job description

PGIM is seeking a Senior Data Engineer for the FM Management Reporting team to build and optimize data pipelines, data lakes and analytics-ready datasets. You will collaborate with architects, data scientists and analysts to deliver high-quality code and scalable solutions.

The role involves applying modern tools like Spark, SQL, Python, and AWS services, with emphasis on data reliability, processing, and governance in a financial services context.