Engineer focusing on data engineering in Google Cloud Platform. Developing and maintaining data pipelines with governance on information quality.
About the role
- Big Data Engineer optimizing scalable data solutions using Hadoop, PySpark, and Hive at Citi. Responsible for building ETL pipelines and ensuring data quality in a hybrid work environment.
Responsibilities
- Design, develop, and maintain efficient and scalable Big Data solutions using PySpark, Apache Hive, and Hadoop ecosystem tools
- Implement and optimize ETL processes and data warehousing solutions
- Conduct in-depth data analysis and troubleshoot complex data issues
- Optimize Big Data workflows, including Spark job tuning and Hive query optimization
- Perform rigorous unit testing and validation of data pipelines
- Collaborate with data scientists, analysts, and other engineers
Requirements
- Extensive experience in designing, developing, and optimizing scalable data solutions using the Hadoop ecosystem
- Strong focus on PySpark and Hive
- Strong Python knowledge
- Implement and optimize ETL (Extract, Transform, Load) processes and data warehousing solutions
- Conduct in-depth data analysis
- Optimize Big Data workflows
- Perform rigorous unit testing
- Collaborate with data scientists, analysts, and other engineers
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Remote work options
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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