Senior Data Engineer

Prudential Financial

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Quick summary

Work type: On-site
Location: Newark, NJ
Salary: $104,000–$171,600 / yr
Employment: Full-time
Posted: 81 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $164k

This role $138k

$92k $214k

below market most similar roles pay here above market

This role pays less than 69% of similar roles. Most pay $126,800–$202,120 — the blue band above. At the midpoint, this role pays about $138k versus about $164k 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 44 open roles on FindRole.

Listed pay typically runs $123,700–$202,050 across 18 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, you will partner with architects, machine learning engineers, and data scientists to improve financial data lakes. Your primary responsibilities include analyzing, designing, developing, and maintaining high-quality data pipelines to drive platform delivery and solve sophisticated business problems. You will build and optimize storage systems, conduct complex data analysis, and prepare data for predictive modeling. The role requires proficiency in Python, R, SQL, Java, Scala, Pyspark/Apache Spark, and Shell scripting. You will also utilize tools such as AWS Redshift, Snowflake, Kinesis, Kafka, Airflow, and Tableau. Key technical competencies include experience with DevOps automation, full software development life cycle practices, data ingestion, and infrastructure as code frameworks like Ansible and CloudFormation.

What does a Data Engineer earn?

Median $159000 from 203 postings across 58 companies.

See salary data

Skills

Python SQL Apache Spark Pyspark Java Scala R AWS Snowflake Redshift Airflow Kafka Kinesis Tableau Power BI Ansible CloudFormation Lambda Step Functions AWS Glue NoSQL DevOps Shell scripting

What you'll do

Build and optimize data pipelines, logic, and storage systems using modern design patterns.
Develop high-quality, well-documented, and efficient code that adheres to company standards.
Conduct complex data analysis and prepare data for prescriptive and predictive modeling.
Combine raw information from different sources to enhance data acquisition and reliability.
Write unit, integration, and functional automation tests to resolve quality assurance issues.
Manage data storage and delivery using relational, NoSQL, and graph databases.
Implement serverless data pipelines using AWS Glue, Lambda, and Step Functions.
Use programming languages including Python, R, SQL, Java, Scala, and Pyspark.

What we're looking for

Bachelor of Computer Science or Engineering or experience in related fields.
Experience in working with DevOps automation tools and practices.
Knowledge of the full software development life cycle (SDLC).
Proficiency in programming languages including Python, R, SQL, Java, Scala, Pyspark/Apache Spark, and Shell scripting.
Experience with data ingestion, integration, transformation, and moving data from multiple sources to analytics platforms.
Experience with database management systems including relational, NoSQL, Graph, AWS Redshift, and Snowflake.
Knowledge of AWS architectural principles, core services, and Infrastructure as Code frameworks like Ansible or CloudFormation.
Experience with serverless data pipeline development using AWS Glue, Lambda, and Step functions (preferred).

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