Application Developer- Python Spark - Assistant Vice President at Citi

Pune, maharashtra, India -

Full Time

Start Date

Immediate

Expiry Date

09 Aug, 26

Salary

0.0

Posted On

11 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Apache Spark, HDFS, Hive, SQL, Unix/Linux, Shell Scripting, Scala, Big Data Architecture, AI Prompting, SDLC, Unit Testing

Industry

Financial Services

Description

Responsibilities • Demonstrated analytical and problem-solving skills. Application performance tuning, troubleshooting experience and the implementation of these skills in Big Data domain. • Comfortable working with large data volumes and be able to demonstrate a firm understanding of logical data structures and analysis techniques. • Minimum 2 years’ experience in Big data technologies like HDFS, Map Reduce, YARN, Apache Spark, Hive. • Familiarity with data formats like Avro, Parquet, CSV, JSON. • Working experience with AI tools and have understand about efficient use of AI and writing prompts to get the solution implemented. • Strong systems analysis, design and architecture fundamentals, Unit Testing and other SDLC activities. • Understanding fundamental design principles behind a scalable application. • Experience in working with UNIX/LINUX and shell scripting. • Good knowledge of database principles, practices with SQL. • Application performance tuning, troubleshooting experience and the implementation of these skills in Big Data domain. Good to Have: • Agile/Scrum methodology experience is required. • Experience in SCMs like GIT and tools like JIRA. • Experience in No SQL databases. • Familiarity with build tools such as Maven and continuous integration like Jenkins/Team City. • Familiarity with cloud and container technologies. • Experience real time data processing - Kafka. Responsibilities: • Translate application storyboards and use cases into functional applications. • Design, build, and maintain efficient, reusable, and reliable Python/Scala code. • Ensure the best possible performance, quality, and responsiveness of the applications. • Identify bottlenecks and bugs, and devise solutions to these problems. • Develop high performance & low latency components to run Spark clusters. • Interpreting functional requirements into design approaches those can be served through Big Data platform. • Collaborate and partner with Global Teams based across different locations. • Be able to propose best practices and standards. • Perform the testing of software prototypes and transfer to the operational team. • Processing of data using Hive, Impala. • Performing analysis of large data sets and derive insights. Qualifications: 7 to 10 Years of strong experience with one or more programming languages (Python/Spark). ------------------------------------------------------ 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. ------------------------------------------------------ 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.

Responsibilities

Design, build, and maintain high-performance Python and Scala applications within a Big Data environment. Translate functional requirements into scalable technical designs and collaborate with global teams to optimize Spark clusters.