Citi – Python Big Data Developer

The Python Big Data Developer role at Citi is designed for experienced technology professionals who can combine Python development, big data engineering, automation, and production support to build and maintain reliable enterprise-scale technology solutions. Based in Pune, this position sits within Citi’s Technology and Applications Development organization and focuses on supporting critical data platforms used in the banking and financial services environment. The role requires hands-on expertise in Python scripting, Unix/Linux, Shell scripting, SQL, and big data technologies including Hadoop, Hive, and PySpark. Professionals in this position will contribute to automation initiatives, batch processing, data analysis, operational monitoring, and application stability. The opportunity is particularly relevant for Python developers and data engineers who want to apply their technical skills to large-scale financial technology systems.

A major part of the position involves ensuring that business-critical data processing and application workflows operate reliably. The Python Big Data Developer will develop automation utilities, monitor scheduled batch processes through AutoSys, investigate production incidents, and perform root-cause analysis when problems occur. The role also involves working with SQL and Oracle databases for data validation, reconciliation, troubleshooting, and analysis, while using technologies such as Hive, Hadoop, and PySpark to process and work with large datasets. Developers will collaborate with business, development, infrastructure, and support teams to resolve issues and maintain operational continuity. This combination of software development and production support makes the role suitable for professionals who enjoy both building technical solutions and solving real-world operational problems in a fast-paced banking technology environment.

Beyond development and data processing, the position emphasizes structured application support, documentation, testing, and continuous improvement. The developer will create and maintain operational runbooks, support procedures, and technical documentation while managing incidents, service requests, defects, and change records through tools such as JIRA. Unit testing of automation scripts and support utilities is also part of the role, helping ensure that solutions are dependable before being introduced into production environments. Experience with Ab Initio, Control Center, Control-M, ETL development, data integration, data warehousing, CI/CD, and DevOps can provide an additional advantage. For professionals with experience in banking, financial services, regulatory reporting, or finance technology, this opportunity offers a chance to work on technology platforms where data accuracy, system reliability, and operational stability are particularly important.

Roles & Responsibilities

1. Develop Python automation solutions for recurring operational and data-processing activities, creating reliable scripts that reduce manual intervention and improve efficiency across enterprise technology environments.
2. Build and maintain Shell scripts in Unix/Linux environments to automate operational tasks, support application workflows, and assist with monitoring and maintenance activities.
3. Monitor enterprise batch processing environments using AutoSys, ensuring scheduled workflows execute correctly and identifying failed, delayed, or interrupted jobs that require investigation.
4. Troubleshoot production incidents by analyzing application behavior, logs, data, and processing workflows, identifying root causes, and implementing corrective and preventive solutions.
5. Work with Big Data technologies such as Hadoop, Hive, and PySpark to support large-scale data processing, analysis, transformation, and troubleshooting activities across enterprise data platforms.
6. Perform SQL-based data validation and reconciliation using SQL and Oracle databases to investigate discrepancies, verify processing results, troubleshoot data-related issues, and maintain data accuracy.
7. Develop and execute unit tests for Python automation scripts and support utilities, identifying defects early and ensuring that newly developed solutions perform according to expected requirements.
8. Monitor ETL workflows and data pipelines, coordinating with development and support teams when processing failures occur and helping restore affected workflows within required operational timelines.
9. Maintain technical documentation and runbooks covering application support procedures, troubleshooting steps, operational processes, and recurring issues so that support activities remain consistent and efficient.
10. Manage technology incidents and service requests using JIRA and related tools, maintaining accurate records for incidents, defects, changes, and other application-support activities.
11. Collaborate with business, development, infrastructure, and support teams to understand technical problems, coordinate resolution activities, communicate progress, and maintain application stability.
12. Support continuous improvement initiatives by identifying opportunities for automation, better monitoring, improved data integration, stronger operational controls, and more efficient production-support processes.

Requirements & Eligibility

1. Professional Experience: Candidates should have approximately 3–6 years of hands-on experience in Python scripting and automation development, with practical exposure to enterprise application or data environments.
2. Python Development: Strong Python programming skills are essential, particularly for developing automation scripts, support utilities, data-processing solutions, and reusable components that can operate reliably in production environments.
3. Unix/Linux & Shell Scripting: Candidates should have strong knowledge of Unix or Linux operating systems and Shell scripting, including the ability to automate system-level activities and troubleshoot scripts and application processes.
4. AutoSys Scheduling: Hands-on experience with AutoSys is required for scheduling and monitoring enterprise batch jobs. Candidates should understand job dependencies, failures, scheduling workflows, and operational monitoring.
5. SQL & Oracle: Strong SQL knowledge and practical experience with Oracle databases are required for data validation, reconciliation, investigation, querying, and troubleshooting. Candidates should be comfortable working with complex datasets and identifying inconsistencies.
6. Big Data Technologies: Practical exposure to Hadoop, Hive, and PySpark is important. Candidates should understand large-scale data processing concepts and be capable of working with distributed data environments and analytical workloads.
7. Production Support: Experience supporting production applications, batch operations, ETL workflows, or enterprise data platforms is essential. Candidates should be comfortable handling incidents, investigating failures, and working within structured support processes.
8. Banking & Financial Services Knowledge: Experience in the banking, financial services, or finance technology domain is required for this position. Familiarity with financial data, enterprise banking systems, or regulated technology environments can be particularly valuable.
9. Problem-Solving & Analytical Skills: Strong analytical thinking is expected, especially when investigating production issues, identifying root causes, validating data, and developing preventive solutions rather than simply addressing symptoms.
10. Additional Technical Skills: Experience with Ab Initio, Ab Initio Control Center, Control-M, ETL development, data integration, incident/change/problem management, release support, data warehousing, CI/CD, or DevOps can strengthen a candidate's profile, although these are listed as preferred or additional skills rather than the core mandatory requirements.

Expected Salary

For a Python Big Data Developer with 3–6 years of experience in Pune, a realistic market-oriented salary expectation would generally be around ₹12 lakh to ₹25 lakh per year, with the exact compensation depending on experience, technical depth, Citi's internal level, and the candidate's expertise in Python, PySpark, Big Data, and financial technology. Available Citicorp salary data for Pune places Big Data Engineer compensation around ₹12 lakh–₹27 lakh annually, while senior data engineering roles can extend higher.