Job description

We are seeking a highly skilled and motivated Senior Data Platform Engineer, AVP (Python/PySpark, Microsoft SSIS, SQL Server, ETL & Database Development) to design, develop, enhance, and support robust, scalable, and high-performance data processing solutions. The ideal candidate will combine strong hands-on expertise in Python/PySpark, SQL Server, ETL/data pipelines, Microsoft SSIS, and large-scale data platforms , with experience troubleshooting production data applications, optimizing database performance, and working across enterprise data environments. The candidate will be working independently on complex assignments while collaborating with engineering , infrastructure, and business teams. Responsibilities: • Data Pipeline & ETL Development: Design, develop, test, and support scalable ETL/data-processing pipelines using Python/PySpark, Microsoft BI/SSIS, SQL, and related technologies. • SQL Server Development: Develop and optimize complex SQL queries, stored procedures, functions, data transformations, and database objects for high-volume applications. • Database Performance: Identify and resolve query and database performance issues through execution-plan analysis, indexing, query optimization, statistics, and appropriate database design techniques. • Large-Scale Data Processing: Develop and support solutions processing large data volumes across SQL Server and distributed data platforms. • Data Architecture & Modeling: Apply relational, dimensional, and data-warehouse modeling principles to build scalable and maintainable data solutions. • Production Support & Troubleshooting: Analyze failed jobs, data-quality issues, performance problems, and production incidents; perform root-cause analysis and implement sustainable resolutions. • Job Scheduling & Automation: Develop and support enterprise batch-processing workflows using scheduling/orchestration platforms such as AutoSys. • Big Data Platforms: Work with Hadoop ecosystem technologies including HDFS, Hive and related distributed-processing technologies. • Data Quality & Reconciliation: Implement validation, reconciliation, exception handling, logging, monitoring, and data-quality controls within data pipelines. • Code Quality: Participate in code reviews and enforce development standards for SQL, Python/PySpark, ETL, and data-processing components. • DevOps: Use Git-based source control and participate in CI/CD processes; work with container technologies such as Docker/Kubernetes where applicable. • Security: Follow secure data-development practices, access-control requirements, encryption standards, and organizational security policies. • Technical Collaboration: Work closely with application developers, infrastructure teams, business teams, and other technology groups to design and deliver solutions. • Continuous Improvement & AI: Evaluate new technologies and leverage approved AI-assisted development tools to improve code quality, troubleshooting, refactoring, and developer productivity. • Appropriately assess risk when business decisions are made, demonstrating consideration for the firm’s reputation and safeguarding the firm, its clients, and assets while complying with applicable laws, rules, regulations, and policies. Recommended Qualifications: • 4+ years of relevant experience in data engineering, application development, database development, or related technology roles. • Strong hands-on experience with Python and PySpark for large-scale data processing and ETL development. • Strong proficiency in SQL/T-SQL and relational database technologies, preferably Microsoft SQL Server. • Experience developing and supporting complex SQL queries, stored procedures, database objects, and high-volume data-processing solutions. • Strong understanding of SQL Server performance tuning, including query execution plans, indexing, statistics, joins, locking/blocking, and query optimization. • Experience with Microsoft BI/SSIS or comparable enterprise ETL technologies. • Experience working with large datasets and distributed data platforms such as Hadoop/HDFS/Hive. • Strong understanding of ETL architecture, data warehousing, dimensional modeling, and relational/3NF modeling. • Experience implementing data-quality checks, reconciliation, audit controls, exception handling, and production monitoring. • Experience with enterprise scheduling/orchestration tools such as AutoSys. • Experience with Git, CI/CD, and modern development practices. • Familiarity with Docker/Kubernetes is preferred. • Familiarity with NoSQL technologies such as MongoDB is beneficial. • Strong analytical, troubleshooting, communication, and problem-solving skills. • Ability to work independently on complex technical assignments while collaborating effectively across teams. • Experience mentoring or providing technical guidance to other developers Education: • Bachelor’s degree/University degree or equivalent experience ------------------------------------------------------ Job Family Group: Technology ------------------------------------------------------ Job Family: Applications Development ------------------------------------------------------ Time Type: Full time ------------------------------------------------------ Primary Location: Irving Texas United States ------------------------------------------------------ Primary Location Full Time Salary Range: $107,120.00 - $160,680.00 In addition to salary, Citi’s offerings may also include, for eligible employees, discretionary and formulaic incentive and retention awards. Citi offers competitive employee benefits, including: medical, dental & vision coverage; 401(k); life, accident, and disability insurance; and wellness programs. Citi also offers paid time off packages, including planned time off (vacation), unplanned time off (sick leave), and paid holidays. For additional information regarding Citi employee benefits, please visit citibenefits.com. Available offerings may vary by jurisdiction, job level, and date of hire. ------------------------------------------------------ Most Relevant Skills Please see the requirements listed above. ------------------------------------------------------ Other Relevant Skills For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------ Anticipated Posting Close Date: Oct 05, 2026 ------------------------------------------------------ Automated Processing and AI We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi. Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details. Illinois residents – AI Notice and Right ------------------------------------------------------ Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi . View Citi’s EEO Policy Statement and the Know Your Rights poster.

Requirements

Must-haves

The candidate will be working independently on complex assignments while collaborating with engineering , infrastructure, and business teams.
Data Pipeline & ETL Development: Design, develop, test, and support scalable ETL/data-processing pipelines using Python/PySpark, Microsoft BI/SSIS, SQL, and related technologies.
SQL Server Development: Develop and optimize complex SQL queries, stored procedures, functions, data transformations, and database objects for high-volume applications.
Database Performance: Identify and resolve query and database performance issues through execution-plan analysis, indexing, query optimization, statistics, and appropriate database design techniques.
Large-Scale Data Processing: Develop and support solutions processing large data volumes across SQL Server and distributed data platforms.
Data Architecture & Modeling: Apply relational, dimensional, and data-warehouse modeling principles to build scalable and maintainable data solutions.
Production Support & Troubleshooting: Analyze failed jobs, data-quality issues, performance problems, and production incidents; perform root-cause analysis and implement sustainable resolutions.
Job Scheduling & Automation: Develop and support enterprise batch-processing workflows using scheduling/orchestration platforms such as AutoSys.
Big Data Platforms: Work with Hadoop ecosystem technologies including HDFS, Hive and related distributed-processing technologies.
Data Quality & Reconciliation: Implement validation, reconciliation, exception handling, logging, monitoring, and data-quality controls within data pipelines.
Code Quality: Participate in code reviews and enforce development standards for SQL, Python/PySpark, ETL, and data-processing components.
DevOps: Use Git-based source control and participate in CI/CD processes; work with container technologies such as Docker/Kubernetes where applicable.
Security: Follow secure data-development practices, access-control requirements, encryption standards, and organizational security policies.
Technical Collaboration: Work closely with application developers, infrastructure teams, business teams, and other technology groups to design and deliver solutions.
Continuous Improvement & AI: Evaluate new technologies and leverage approved AI-assisted development tools to improve code quality, troubleshooting, refactoring, and developer productivity.
4+ years of relevant experience in data engineering, application development, database development, or related technology roles.
Strong hands-on experience with Python and PySpark for large-scale data processing and ETL development.
Strong proficiency in SQL/T-SQL and relational database technologies, preferably Microsoft SQL Server.
Experience developing and supporting complex SQL queries, stored procedures, database objects, and high-volume data-processing solutions.
Strong understanding of SQL Server performance tuning, including query execution plans, indexing, statistics, joins, locking/blocking, and query optimization.
Experience with Microsoft BI/SSIS or comparable enterprise ETL technologies.
Experience working with large datasets and distributed data platforms such as Hadoop/HDFS/Hive.
Strong understanding of ETL architecture, data warehousing, dimensional modeling, and relational/3NF modeling.

Nice-to-haves

Familiarity with Docker/Kubernetes is preferred.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

pythonsqlci/cddockerkubernetesaiaccessibility

Platform: eightfold
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Wellness