Python and Apache Spark Big Data Engineer - Assistant Vice President
At a glance
VP-level Data Engineering role at Citi. Pune Maharashtra India · full-time.
Pay not stated Data Engineering salary
dataroles summary, based on the employer's posting.
What you'll do
- Turn application stories and use cases into working software, then build and maintain dependable Python or Scala code
- Improve application speed and responsiveness by finding bottlenecks, fixing defects, and tuning Spark components
- Translate functional needs into Big Data designs, then process data with Hive, Impala, and HBASE
- Analyze large datasets for insights, test software prototypes, and hand completed work to operations
- Work with global teams to establish practices and standards for application development
What you bring
- You have between eight and twelve years of experience
- You bring strong Python or Spark skills and experience with Big Data technologies such as HDFS, Map Reduce, or YARN
- You understand SQL, data structures, scalable application design, and performance tuning in Big Data environments
- You have experience with UNIX or Linux, shell scripting, and software testing and development practices
Who this fits
This role suits an experienced engineer focused on Python, Spark, and large-scale data processing. It is a hybrid position in India and involves collaboration with teams in different locations.
From the employer
Experience Range - 8 to 12 years
Strong experience with one or more programming languages (Python/Spark).
• 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.
• Experience in Big data technologies like HDFS, Map Reduce, YARN, Apache Spark, Hive.
• Familiarity with data formats like Avro, Parquet, CSV, JSON.
• 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 & HBASE.
• Performing analysis of large data sets and derive insights.
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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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