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We are seeking a highly experienced and technically proficient Senior Developer to join our team at Citi. The successful candidate will play a critical role in designing, developing, and optimizing data-driven solutions using Oracle SQL/PL SQL and Python with PySpark. This role requires deep expertise in database programming, data processing, and an ability to work with large datasets within a financial services context.
Job Responsibility:
Design, develop, and maintain complex Oracle SQL and PL/SQL packages, stored procedures, functions, and triggers for critical business applications
Develop and implement robust data processing pipelines using Python and PySpark for large-scale data ingestion, transformation, and analysis
Optimize existing SQL queries, PL/SQL code, and PySpark jobs for performance, scalability, and efficiency
Collaborate with data architects, data scientists, and business stakeholders to understand data requirements and translate them into technical solutions
Ensure data quality, integrity, and security across all developed solutions
Participate in all phases of the software development lifecycle, including requirements gathering, design, coding, testing, deployment, and support
Troubleshoot and resolve complex database and data pipeline-related issues
Provide technical guidance and mentorship to junior developers
Stay abreast of new technologies and best practices in Oracle database development, Python, and big data processing (Spark)
Requirements:
Bachelor's or Master's degree in Computer Science, Engineering, Information Technology, or a related field
10+ years of progressive experience in software development, with a strong focus on Oracle database development and data engineering
Proven experience as a Senior Developer in a large enterprise environment, preferably within financial services
Strong domain knowledge and experience on the functionality of Customer Due Diligence (CDD) or Know Your Customer (KYC) platforms
Expert-level proficiency in Oracle SQL and PL/SQL, including performance tuning and advanced database concepts
Strong expertise in Python programming, particularly with PySpark for big data processing
Extensive experience with data warehousing concepts, ETL/ELT processes, and data modeling
Proficiency with version control systems (e.g., Git)
Nice to have:
Experience with scripting languages (e.g., Shell scripting)
Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services
Experience with job scheduling tools (e.g., Control-M, Airflow)
Knowledge of data governance and data quality best practices