Responsibilities:
- Develop, test, and deploy high-quality Python code for data migration, data profiling, and data processing.
- Design and implement scalable solutions for working with large and complex datasets, ensuring data integrity and performance.
- Utilize PySpark for distributed data processing and analytics on large-scale data platforms.
- Develop and optimize SQL queries for various database systems, including Oracle, to extract, transform, and load data efficiently.
- Integrate Python applications with JDBC-compliant databases (e.g., Oracle) for seamless data interaction.
- Implement data streaming solutions to process real-time or near real-time data efficiently.
- Perform in-depth data analysis using Python libraries, especially Pandas, to understand data characteristics, identify anomalies, and support profiling efforts.
- Collaborate with data architects, data engineers, and business stakeholders to understand requirements and translate them into technical specifications.
- Contribute to the design and architecture of data solutions, ensuring best practices in data management and engineering.
- Troubleshoot and resolve technical issues related to data pipelines, performance, and data quality.
Qualifications:
- 4-7 years of relevant experience in the Financial Service industry
- Strong Proficiency in Python:
- Excellent command of Python programming, including object-oriented principles, data structures, and algorithms.
- PySpark Experience:
- Demonstrated experience with PySpark for big data processing and analysis.
- Database Expertise:
- Proven experience working with relational databases, specifically Oracle, andconnecting applications using JDBC.
- SQL Mastery:
- Advanced SQL querying skills for complex data extraction, manipulation, andoptimization.
- Big Data Handling:
- Experience in working with and processing large datasets efficiently.
- Data Streaming:
- Familiarity with data streaming concepts and technologies (e.g., Kafka, SparkStreaming) for processing continuous data flows.
- Data Analysis Libraries:
- Proficient in using data analysis libraries such as Pandas for data manipulationand exploration.
- Software Engineering Principles:
- Solid understanding of software engineering best practices,including version control (Git), testing, and code review.
- Problem-Solving:
- Intuitive problem-solver with a self-starter mindset and the ability to work independently and as part of a team.
Education:
- Bachelor’s degree/University degree or equivalent experience
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
Preferred Skills & Qualifications (Good to Have):
Experience in developing and maintaining reusable Python packages or libraries for data engineering tasks.
Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their data services.
Knowledge of data warehousing concepts and ETL/ELT processes.
Experience with CI/CD pipelines for automated deployment.
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Job Family Group:
Technology------------------------------------------------------
Job Family:
Applications Development------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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Citi Chennai, Tamil Nadu, IND Office
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