Data Solutions Engineer, Assistant Vice President

Citi

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Irving, TXJacksonville, FL
Salary
$107,120–$160,680 / yr
Employment
Full-time
Posted
1 day ago
Freshness
Confirmed live today
Closes
Oct 28, 2026

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $160k
This role $134k
$96k most similar roles pay here $208k

This role pays less than 66% of similar roles. Most pay $126,800–$192,500 — the shaded band above. At the midpoint, this role pays about $134k versus about $160k 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 271 open roles on FindRole.

Listed pay typically runs $125,760–$188,640 across 255 roles with salary data.

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View all roles at Citi

At a glance

TL;DR · Data Solutions Engineer, Assistant Vice President

Data Solutions Engineer, Assistant Vice President will join a team building data pipelines and platforms that support analytics, reporting, and data science across a global financial institution. This hands-on role involves building and maintaining scalable, high-performance data pipelines to support machine learning capabilities and developing Big Data solutions using Apache Spark, Hadoop, and cloud-native services. The engineer will collaborate with architects and data scientists to implement platform designs while applying data quality controls and automation for governance. Key technologies include Python, PySpark, Kafka, Hive, Docker, and Kubernetes, with additional experience in Snowflake, Databricks, Scala, or Java being beneficial. The role focuses on solving complex data challenges at enterprise scale, including migrating legacy platforms and managing large volumes of data to support business decision-making through modern cloud infrastructure and robust distributed processing frameworks.

What you'll do

  • Build and maintain scalable, high-performance data pipelines for analytics, reporting, and machine learning.
  • Develop Big Data solutions using Apache Spark, Hadoop, and cloud-native services to manage large volumes of data.
  • Engineer data pipelines in partnership with data scientists to support advanced analytics use cases.
  • Implement data quality controls, monitoring, and automation to ensure governance and auditability standards.
  • Research and recommend emerging technologies to improve platform performance, scalability, and maintainability.
  • Mentor junior engineers by sharing technical best practices and knowledge within the team.
  • Participate in Agile delivery activities including sprint planning, testing, and production support.

What we're looking for

  • Must have 5+ years of experience in data engineering, software engineering, or a related discipline.
  • Must have practical experience designing and building large-scale data pipelines and distributed processing solutions in production environments.
  • Must have hands-on development experience using Python and Apache Spark (PySpark) to process and transform data at scale.
  • Must have experience with cloud-based data platforms, specifically AWS or Google Cloud Platform (GCP).
  • Must have working knowledge of data warehousing, data modeling, and distributed processing frameworks like Spark, Hadoop, Kafka, or Hive.
  • Must be familiar with containerization tools such as Docker and Kubernetes.
  • Experience using Snowflake/Databricks for cloud data warehousing and analytics (preferred).
  • Authorized to work in the U.S for this position.

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