Senior Data Platform Engineer

Citi

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Irving, TXJacksonville, FLTampa, FL
Salary
$107,120–$160,680 / yr
Employment
Full-time
Posted
4 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $183k
This role $134k
$94k most similar roles pay here $232k

This role pays less than 85% of similar roles. Most pay $151,000–$215,250 — the shaded band above. At the midpoint, this role pays about $134k versus about $183k 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 · Senior Data Platform Engineer

The Senior Data Platform Engineer, AVP (Python/PySpark, Microsoft SSIS, SQL Server, ETL & Database Development) joins the technology team to design, develop, and support robust, high-performance data processing solutions. This role involves building scalable ETL pipelines using Python, PySpark, and Microsoft SSIS while managing complex SQL Server objects like stored procedures and functions. The engineer will perform database performance tuning through execution-plan analysis, manage large-scale data volumes across Hadoop, HDFS, and Hive environments, and implement automated workflows using AutoSys. Key responsibilities include ensuring data quality through reconciliation and monitoring, participating in code reviews, and utilizing Git for CI/CD processes. The role addresses the technical challenge of managing high-volume data processing and infrastructure within enterprise environments, requiring expertise in relational and dimensional modeling to solve complex data architecture problems across distributed platforms.

What you'll do

  • Design, develop, and support scalable ETL pipelines using Python, PySpark, and Microsoft SSIS.
  • Develop and optimize complex SQL queries, stored procedures, and database objects for high-volume applications.
  • Resolve database performance issues through execution-plan analysis, indexing, and query optimization techniques.
  • Build scalable data solutions using relational, dimensional, and data-warehouse modeling principles.
  • Perform root-cause analysis and provide production support for failed jobs and data quality issues.
  • Manage enterprise batch-processing workflows using orchestration platforms like AutoSys.
  • Implement data validation, reconciliation, and monitoring controls within automated data pipelines.
  • Maintain code quality through peer reviews and integration into CI/CD pipelines using Git.

What we're looking for

  • Bachelor's degree or equivalent experience.
  • 4+ years of relevant experience in data engineering, application development, or database development.
  • Strong hands-on experience with Python and PySpark for large-scale data processing and ETL development.
  • Proficiency in SQL/T-SQL and relational databases, specifically Microsoft SQL Server.
  • Experience with Microsoft BI/SSIS or comparable enterprise ETL technologies.
  • Experience with distributed data platforms such as Hadoop, HDFS, and Hive.
  • Strong understanding of ETL architecture, data warehousing, and dimensional modeling.
  • Familiarity with Docker/Kubernetes (preferred); familiarity with NoSQL technologies like MongoDB (beneficial).

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