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Pune · On-site · 8-11 Yrs · Oct 20
Investment & Asset Management · 10000+ Employees · New York, US
Citi is more than a global financial services company. It’s an engine for progress. Join us, and you’ll have the chance to get involved in progress in all its shapes and forms, right across the world. From the micro to the macro, from Australia to Zambia, the work we do has real positive impact. Wherever you are and whatever you do, progress starts here. We’ve built a world famous, trusted brand over 200 years of continuously evolving financial services. And today, our influence continues to grow: with financial operations in 160 countries and 100 currencies. We have 200 million different clients, including some of the biggest names in the industries, sectors, businesses and governments that we serve every day. It all adds up to an exciting place to be for talented, ambitious people who want to build a truly remarkable career.
Hiring: Engineering
What employees say
+ good medical insurance good pay
− micromanagement old school management office politics
More reviews on the company profile.
Interview experience · Operations Associate
Interview was slow . The interviewee scheduled me interview and didn't join the call. After waiting for 30 minutes, i sent a mail to hr and then she called the technician team and then they had joined the call. Also seem
Average difficulty · Chennai · 965 reports
More interview insightsJob description
Overview
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.
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.
- 8+ 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.
Qualifications
- The candidate will be working independently on complex assignments while collaborating with engineering , infrastructure, and business teams.
Education
- Bachelor’s degree/University degree or equivalent experience.
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Last updated 24 October 2026
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