Senior Data Engineer

Prudential Financial

Quick summary

Work type: On-site
Location: Newark, NJ
Salary: $104,000–$171,600 / yr
Posted: 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $175k

This role $138k

$91k most similar roles pay here $230k

This role pays less than 77% of similar roles. Most pay $140,418–$209,187 — the shaded band above. At the midpoint, this role pays about $138k versus about $175k 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 45 open roles on FindRole.

Listed pay typically runs $133,600–$204,100 across 41 roles with salary data.

Most-posted roles

View all roles at Prudential Financial

At a glance

TL;DR · Senior Data Engineer

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As a Senior Data Engineer on the FM Management Reporting team at Prudential, you will collaborate with architects and data scientists to build high-quality data pipelines that enhance financial data lakes. Your daily tasks include developing efficient code, conducting complex data analysis, and integrating diverse data sources to improve reliability and efficiency. You will use programming languages like Python, R, SQL, Java, Scala, and Pyspark, while also working with tools such as AWS Redshift, Snowflake, Kinesis, Kafka, and Airflow. This role requires a strong understanding of DevOps practices, cloud computing, and data security principles to solve sophisticated business problems and deliver innovative solutions that delight customers.

Skills

Python R SQL Java Scala Pyspark Apache Spark Shell scripting AWS Redshift Snowflake Kinesis Kafka Airflow CloudFormation AWS Unit testing CI/CD Tableau Power BI

What you'll do

Build and optimize high-quality data pipelines and storage systems using modern design patterns.
Develop efficient, well-documented code adhering to Prudential’s coding standards.
Conduct complex data analysis and prepare data for advanced modeling techniques.
Collaborate with cross-functional teams to enhance data acquisition and transformation processes.
Write unit tests and automate functional testing to ensure software quality.
Identify opportunities for technology innovation and coach team members on new practices.

What we're looking for

5+ years of hands-on experience in building and optimizing data pipelines using modern design patterns and coding practices.
Proficiency in Python, R, SQL, Java, Scala, Pyspark/Apache Spark, and Shell scripting for data engineering tasks.
Strong background in database management systems including relational DBs, NoSQL DBs, Graph DBs, AWS Redshift, and Snowflake.
Experience with DevOps automation tools and practices, including knowledge of the full software development life cycle (SDLC).
Excellent problem-solving, communication, and collaboration skills to work effectively in a team environment.

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