Python and Apache Spark Big Data Engineer - Assistant Vice President
Citi (company site, opens in a new tab)8–12 yrsPuneOn-siteDirect career pageEst. 30–50 LPA
Posted 9h ago
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Reach people at Citi
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Citi you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, build, and maintain efficient, reusable, and reliable Python/Scala code for Big Data applications using Spark clusters.
- Analyze and process large datasets using Big Data technologies like Hive, Impala, HBASE; ensure application performance tuning and troubleshooting within Big Data domain.
- Collaborate with global teams to translate functional requirements into scalable Big Data platform solutions; propose best practices and standards.
Minimum Requirements
- 8 to 12 years of experience with strong programming skills in Python and Apache Spark.
- Experience with Big Data technologies: HDFS, Map Reduce, YARN, Apache Spark, Hive and familiarity with data formats like Avro, Parquet, CSV, JSON.
- Proficient in UNIX/Linux environment and shell scripting plus good knowledge of SQL databases and application performance tuning in Big Data.
- Work Experience Required: 8 to 12 years
Ideal Candidate Profile
- Experienced in designing scalable applications and implementing performance optimizations in Big Data environments.
- Comfortable working with large data volumes and translating functional requirements into technical designs within global, distributed teams.
- Familiar with Agile/Scrum, version control tools (GIT), and optionally cloud, container technologies, real-time data processing (Kafka), and CI/CD tools.