Senior ETL Developer Assistant Vice President

Citi

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Tampa, FL
Salary: $96,960–$145,440 / yr
Posted: 10 days ago
Freshness: Confirmed live yesterday
Closes: Nov 1, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $159k

This role $121k

$84k most similar roles pay here $215k

This role pays less than 83% of similar roles. Most pay $133,750–$185,000 — the shaded band above. At the midpoint, this role pays about $121k versus about $159k 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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At a glance

TL;DR · Senior ETL Developer Assistant Vice President

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Senior ETL Developer - Assistant Vice President will join the technology team to design, implement, and optimize distributed data processing jobs for large-scale datasets within the Hadoop Distributed File System. The role involves building Spark applications and developing ETL pipelines using Python to handle data ingestion, cleaning, aggregation, and transformation. You will be responsible for performance optimization of Spark jobs through memory management and partitioning strategies while integrating applications with Hive and Sqoop. Collaborating with data engineers and business stakeholders, you will ensure data accuracy and integrity across various sources. The position requires proficiency in the Hadoop ecosystem, Python, and Spark to solve complex data engineering challenges. Candidates must possess experience in systems analysis, programming, and project management techniques to manage deadlines while troubleshooting job failures and monitoring logs for optimal performance.

Skills

Apache Spark Python HDFS Hadoop ETL Hive Sqoop Data Engineering Data Processing Performance Optimization Partitioning Caching Debugging

What you'll do

Design and implement Spark applications to process and transform large datasets in HDFS.
Develop ETL pipelines using Python for data ingestion, cleaning, aggregation, and transformation.
Optimize Spark jobs by fine-tuning memory management, caching, and partitioning strategies.
Load data from various sources into HDFS while ensuring data accuracy and integrity.
Integrate Spark applications with Hadoop frameworks such as Hive and Sqoop.
Troubleshoot and debug Spark job failures using logs and the Spark UI to identify issues.

What we're looking for

Bachelor's degree, university degree, or equivalent experience.
5-8 years of relevant experience in software development.
Proficiency in Python programming.
Hands-on experience with Apache Spark and Hadoop ecosystems.
Experience designing and optimizing distributed data processing jobs in HDFS.
Experience developing ETL pipelines for data ingestion, cleaning, and transformation.
Knowledge of consulting and project management techniques.
Ability to work under pressure and manage deadlines or changing requirements.

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