Big Data Senior Manager
| Company | Citigroup |
|---|---|
| Location | Tampa, FL, USA, Irving, TX, USA |
| Salary | $113840 – $170760 |
| Type | Full-Time |
| Degrees | |
| Experience Level | Senior, Expert or higher |
Requirements
- At least two years (Over all 10+ hands on Data Engineering experience) of experience building and leading highly complex, technical data engineering teams.
- Experience: 6 to 10+ years of hands-on experience in big data development, focusing on Apache Spark, Scala, and distributed systems.
- Proficiency in Functional Programming: High proficiency in Scala-based functional programming for developing robust and efficient data processing pipelines.
- Proficiency in Big Data Technologies: Strong experience with Apache Spark, Hadoop ecosystem tools such as Hive, HDFS, and YARN, AIRFLOW, DataOps, Data Management.
- Programming and Scripting: Advanced knowledge of Scala and a good understanding of Python for data engineering tasks.
- Data Modeling and ETL Processes: Solid understanding of data modeling principles and ETL processes in big data environments.
- Analytical and Problem-Solving Skills: Strong ability to analyze and solve performance issues in Spark jobs and distributed systems.
- Version Control and CI/CD: Familiarity with Git, Jenkins, and other CI/CD tools for automating the deployment of big data applications.
- Experience with Python.
Responsibilities
- Partner with multiple management teams to ensure appropriate integration of functions to meet goals as well as identify and define necessary system enhancements to deploy new products and process improvements.
- Resolve variety of high impact problems/projects through in-depth evaluation of complex business processes, system processes, and industry standards.
- Provide expertise in area and advanced knowledge of applications programming and ensure application design adheres to the overall architecture blueprint.
- Utilize advanced knowledge of system flow and develop standards for coding, testing, debugging, and implementation.
- Provide in-depth analysis with interpretive thinking to define issues and develop innovative solutions.
- Serve as advisor or coach to mid-level developers and analysts, allocating work as necessary.
Preferred Qualifications
- Real-Time Data Streaming: Experience with streaming platforms such as Apache Kafka or Spark Streaming.
- Python Data Engineering Experience.
- Financial Services Context: Familiarity with financial data processing, ensuring scalability, security, and compliance requirements.
- Leadership in Data Engineering: Proven ability to work collaboratively with teams to develop robust data pipelines and architectures.