The Big Data Engineer is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead applications systems analysis and programming activities.
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
- Develop comprehensive knowledge of how areas of business, such as
architecture and infrastructure, integrate to accomplish business goals
- 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
- Appropriately assess risk when business decisions are made, demonstrating
consideration for the firm's reputation and safeguarding Citigroup, its clients
and assets, by driving compliance with applicable laws, rules and regulations,
adhering to Policy, applying sound ethical judgment regarding personal
behavior, conduct and business practices, and escalating, managing and
reporting control issues with transparency.
Qualifications:
- 5+Years of Expirience in Big Data Engineering (PySpark)
- Data Pipeline Development: Design, build, and maintain scalable ETL/ELT
- pipelines to ingest, transform, and load data from multiple sources.
- Big Data Infrastructure: Develop and manage large-scale data processing
- systems using frameworks like Apache Spark, Hadoop, and Kafka.
- Proficiency in programming languages like Python, or Scala.
- Strong expertise in data processing frameworks such as Apache Spark,
- Hadoop.
- Expertise in Data Lakehouse technologies (Apache Iceberg, Apache Hudi,
- Trino)
- Experience with cloud data platforms like AWS (Glue, EMR, Redshift), Azure
- (Synapse), or GCP (BigQuery).
- Expertise in SQL and database technologies (e.g., Oracle, PostgreSQL, etc.).
- Experience with data orchestration tools like Apache Airflow or Prefect.
- Familiarity with containerization (Docker, Kubernetes) is a plus
Good to Have Skills:
- Distributed caching solutions (Hazelcast or Redis)
- Prior experience with building distributed, multi-tier applications is highly desirable.
- Experience with building apps which are highly performant and scalable will be great
Education:
• Bachelor’s degree/University degree or equivalent experience
• Master’s degree preferred
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Job Family Group:
Technology------------------------------------------------------
Job Family:
Applications Development------------------------------------------------------
Time Type:
Full time------------------------------------------------------
Primary Location Full Time Salary Range:
$94,300.00 - $141,500.00------------------------------------------------------
Most Relevant Skills
Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills
For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
Automated Processing and AI
We use automated processing, including artificial intelligence, for our legitimate business interests (or our reasonable and appropriate business purposes) to identify and align the candidate's skills and abilities with a specific job opening. Additionally, if you so choose, or consent, we can match your skills and abilities to other suitable roles at Citi.
Importantly, all our hiring processes and decisions, including determining your suitability for a role, are conducted, checked, and decided by individuals. Our automated processing and AI do not involve relying on automatic or autonomous decision-making. Please refer to any Jurisdictional Considerations, with specific provisions for your country (where relevant) for further details.
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