Senior Data Engineer Vice President

Citi

Confirmed live yesterday High trust
Remote

Quick summary

Work type
Remote
Location
Irving, TX
Salary
$125,760–$188,640 / yr
Posted
51 days ago
Freshness
Confirmed live yesterday
Closes
Sep 22, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $175k
This role $157k
$116k most similar roles pay here $221k

This role pays less than 63% of similar roles. Most pay $138,775–$211,200 — the shaded band above. At the midpoint, this role pays about $157k versus about $175k 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 256 open roles on FindRole.

Listed pay typically runs $140,080–$210,120 across 238 roles with salary data.

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View all roles at Citi

At a glance

TL;DR · Senior Data Engineer Vice President

Senior Data Engineer - Vice President will join a small, high-performing squad as a hands-on contributor to develop, implement, and optimize robust, scalable data solutions within a Hadoop ecosystem and streaming platforms. The role involves building complex data pipelines, managing real-time streaming via Apache Kafka, and developing Spark-based solutions for advanced analytics and reporting. You will be responsible for ensuring data security and governance while integrating AI/ML capabilities into production environments through MLOps initiatives. Key technologies include Python, PySpark, FastAPI, SQL, Unix, and HDFS, alongside tools like Devin and Copilot. The position requires an AI-first mindset to leverage cutting-edge coding tools. This role operates within the banking domain, where you will solve complex data challenges while ensuring compliance with strict regulatory standards and high-performance requirements for real-time data processing.

What does a Data Engineer earn?

Median $183138 from 214 postings across 58 companies.

See salary data

What you'll do

  • Develop and manage complex Hadoop-based data pipelines and real-time streaming solutions using Apache Kafka.
  • Build Spark-based solutions to support near real-time data ingestion, advanced analytics, and reporting.
  • Implement AI/ML models within data pipelines, focusing on feature engineering and production deployment.
  • Execute MLOps initiatives to streamline the machine learning lifecycle through continuous integration and training.
  • Optimize Hadoop clusters and streaming applications for high throughput, low latency, and resource efficiency.
  • Enforce data security and governance policies in compliance with banking sector regulations.
  • Mentor team members and provide technical leadership on big data and AI-first development practices.
  • Take full ownership of end-to-end project delivery from initial concept through testing and deployment.

What we're looking for

  • Bachelor's degree or equivalent experience is required, with a Master's degree preferred.
  • 7+ years of experience developing and optimizing complex Hadoop-based and real-time data platforms.
  • Proficiency in Python, PySpark, FastAPI, Unix, and SQL.
  • Extensive experience with Apache Kafka and other real-time data streaming technologies.
  • Strong knowledge of the Hadoop ecosystem including HDFS, YARN, MapReduce, Hive, HBase, and Spark.
  • Experience with AI/ML lifecycle management, MLOps practices, and utilizing AI coding tools like Devin or Copilot.
  • Proven track record of end-to-end project delivery within the banking or financial services sector.
  • Familiarity with major cloud platforms such as AWS, Azure, and Google Cloud.

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