Officer - Data Engineer (Big Data, Python, PySpark)
Content + Source + Freshness • 14 Dec 2025 • 95% confidence
Offer value
The role presents a strong value due to its alignment with emerging technologies in data engineering and the reputable employer brand of Citi.
- Work with big data technologies like Hadoop and PySpark.
- Flexible hybrid working model.
- Strong alignment with modern banking innovations.
Pros
- Opportunity to work with big data technologies such as Hadoop and Snowflake.
- Hybrid work model offering flexibility.
- Reputable employer with a focus on innovation.
Cons
- Competitive job market for data engineering roles.
- Role may require navigating high-pressure deadlines.
- Limited salary information provided.
Who it's for
Mid-level • Hybrid
Good fit
- Experienced data engineers with strong Python knowledge.
- Candidates familiar with big data processing frameworks.
- Professionals eager to work in financial services.
Not recommended for
- New graduates without relevant work experience.
- Those hesitant about working under tight deadlines.
- Individuals seeking fully remote roles.
Motivation fit
Key skills
About the job
At Citi we’re not just building technology, we’re building the future of banking. Encompassing a broad range of specialties, roles, and cultures, our teams are creating innovations used across the globe. Citi is constantly growing and progressing through our technology, with laser focused on evolving the ways of doing things. As one of the world’s most global banks we’re changing how the world does business.
Shape your Career with Citi
We’re currently looking for a high caliber professional to join our team as 25909874 Officer, Data Engineer -C11- Hybrid based in Pune, India. Being part of our team means that we’ll provide you with the resources to meet your unique needs, empower you to make healthy decision and manage your financial well-being to help plan for your future.
The Data Engineer is accountable for developing high quality data products to support the Bank’s regulatory requirements and data driven decision making. A Data Engineer will serve as an example to other team members, work closely with customers, and remove or escalate roadblocks. By applying their knowledge of data architecture standards, data warehousing, data structures, and business intelligence they will contribute to business outcomes on an agile team.
Responsibilities & Qualifications
5-8 years of relevant experience Big Data: Experience of ‘big data’ platforms such as Hadoop, Hive or Snowflake for data storage and processing.
Data Modeling & Design: Good exposure to data modeling techniques; design, optimization and maintenance of data models and data structures
Languages: Proficient in one or more programming languages commonly used in data engineering such as Python, PySpark
Data Warehousing & Database Management: Understanding of Data Warehousing concepts,
Demonstrated problem-solving and decision-making skills
Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements
Education:
Bachelor’s degree/University degree or equivalent experience
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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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