Principal Data Platform Engineer Vice President

Citi

Remote

Quick summary

Work type: Remote
Location: Irving, TX
Salary: $125,760–$188,640 / yr
Posted: 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $174k

This role $157k

$116k most similar roles pay here $220k

This role pays less than 61% of similar roles. Most pay $145,812–$202,750 — the shaded band above. At the midpoint, this role pays about $157k versus about $174k for comparable roles.

Based on 240 similar postings.

Employer

About Citi

Citi is one of the world’s most trusted financial institutions, proudly serving millions of customers across the United States.

Citi currently has 397 open roles on FindRole.

Listed pay typically runs $125,760–$188,640 across 367 roles with salary data.

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At a glance

TL;DR · Principal Data Platform Engineer Vice President

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As a Full Stack Python Developer at the senior level within our Technology team, you will lead the development of robust and scalable data solutions that drive critical business insights. Your day-to-day responsibilities include architecting complex data processing systems using Python and Pyspark, managing distributed data platforms like Hadoop and Cloudera, and designing highly scalable ETL pipelines for efficient data handling. You will also leverage AI tools to optimize code quality and productivity while ensuring data integrity and security through advanced data modeling principles. Additionally, you will mentor junior developers and implement CI/CD pipelines using Git, Docker, and Kubernetes. This role requires extensive experience with big data technologies, Python scripting, and cloud-native solutions, making it ideal for someone passionate about driving innovation in a high-scale environment.

Skills

Python PySpark Hadoop Cloudera HDFS Hive Pig Sqoop MongoDB ETL CI/CD Git Docker Kubernetes DevOps

What you'll do

Develop and maintain complex data processing solutions using Python/Pyspark.
Architect and manage distributed data processing platforms within the Hadoop ecosystem.
Design and implement highly scalable ETL pipelines for efficient data management.
Ensure data integrity and optimal performance in data warehouse design and development.
Leverage AI tools to enhance code quality and developer productivity through refactoring.
Proficient in CI/CD pipelines, version control systems like Git, and containerization technologies.

What we're looking for

6+ years of experience in Python and big data development.
Expert-level skills in Python/Pyspark for complex data processing.
Extensive experience with Hadoop ecosystem and Cloudera distributions.
Proven ability to architect scalable ETL pipelines and cloud-native solutions.
Understanding of advanced data modeling principles and warehouse design.
Experience with AI tools for code refactoring and optimization.
Proficiency in DevOps practices, version control, and containerization.

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