Time since we first saw it
Day 4
Early. Similar jobs usually come down between day 6 and day 54.
At Citi, jobs usually come down by about day 16.
From 11,494 similar postings that came down, and 1,277 of Citi’s. Coming down is not always a hire.
Senior Data Engineer
Chennai, TN, IN; Pune, MH, IN
Actively hiring, first seen by us 4 days ago- Pay
- Pay not listed
- Work setting
- Not stated
- Employment
Full-time — employment source
Time Type: Full time------------------------------------------------------ Most Relevant Skills
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
What you’ll work on
Full postingRefactor Spark pipelines to Databricks-native architecture, removing Hadoop dependencies
Build and optimize solutions with Delta Lake and Databricks Workflows
Produce low and mid level designs, data models and pipeline patterns
Analyze and improve Spark job performance, simplifying over-engineered pipelines
Develop unit, integration and data validation tests
From the employer’s posting
Refactor and modernize existing Spark pipelines to Databricks native architectures
Build and optimize solutions using Databricks features, including Delta Lake, Databricks Workflows for orchestration
Contribute to low and mid level architecture and design
Analyze, improve Spark job performance and simplify complex or over engineered pipelines
Develop unit, integration, and data validation tests
What you’ll bring
All qualificationsCore experience
- 8+ years in data engineering or distributed systems
- Experience with AWS services and large‑scale distributed data processing
- Experience modernizing or refactoring legacy data platforms into cloud‑based architectures
- Bachelor’s degree/University degree and equivalent experience
- Strong expertise in Apache Spark (ScalaSpark/ JavaSpark / PySpark), Databricks on AWS, and Delta Lake
- Ability to translate architecture into implementable designs
Qualification wording
8+ years in data engineering or distributed systems
Experience with AWS services and large‑scale distributed data processing
Experience modernizing or refactoring legacy data platforms into cloud‑based architectures
Bachelor’s degree/University degree and equivalent experience
Strong expertise in Apache Spark (ScalaSpark/ JavaSpark / PySpark), Databricks on AWS, and Delta Lake
Ability to translate architecture into implementable designs
Education & alternatives
Education: Bachelor’s degree/University degree and equivalent experience ------------------------------------------------------
Posting record
Report an errorActively hiringFirst seen by us 4 days ago, still listed, and not a repost of an earlier posting.
- Status in our records
- Live
- First seen by us
- Nov 3, 20264 days ago
- Recorded sightings
- 4
- Last seen by us
- Nov 7, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Citi is hiring
162 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is picking up
- Takes jobs down quickly
- 5% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- SQL
- AWS
- Databricks
- Delta Lake
- Hadoop
- Spark
- PySpark
Where the posting names them
Strong expertise in Apache Spark (ScalaSpark/ JavaSpark / PySpark), Databricks on AWS, and Delta Lake Experience on SQL Experience with AWS services and large‑scale distributed data processing
We are looking for a highly skilled Senior Data Engineer to contribute to the engineering, modernization, and continuous evolution of data processing platform on Databricks on AWS. While supporting the transition from the legacy Cloudera Hadoop platform to Databricks on AWS, this role will continue to play a key part in enhancing performance, simplifying pipelines, and delivering new capabilities on the Databricks platform over the long term. The ideal candidate is a strong hands‑on Spark engineer with solid design experience, capable of contributing to architectural decisions while leading complex implementation and optimization efforts.
Refactor and modernize existing Spark pipelines to Databricks native architectures Eliminate legacy Hadoop dependencies and adopt cloud native AWS patterns Enhance and extend existing processing logic using optimized Spark (ScalaSpark) on Databricks
8+ years in data engineering or distributed systems Strong expertise in Apache Spark (ScalaSpark/ JavaSpark / PySpark), Databricks on AWS, and Delta Lake Experience on SQL
Experience on SQL Experience with AWS services and large‑scale distributed data processing Modernization & Optimization Experience
1. Platform Engineering & Modernization Refactor and modernize existing Spark pipelines to Databricks native architectures Eliminate legacy Hadoop dependencies and adopt cloud native AWS patterns
Eliminate legacy Hadoop dependencies and adopt cloud native AWS patterns Enhance and extend existing processing logic using optimized Spark (ScalaSpark) on Databricks 2. Databricks Native Development
Enhance and extend existing processing logic using optimized Spark (ScalaSpark) on Databricks 2. Databricks Native Development Build and optimize solutions using Databricks features, including Delta Lake, Databricks Workflows for orchestration and Auto scaling and job clusters
2. Databricks Native Development Build and optimize solutions using Databricks features, including Delta Lake, Databricks Workflows for orchestration and Auto scaling and job clusters 3. Design & Solution Engineering
5. Engineering Standards & Best Practices Follow and contribute to Databricks and Spark engineering standards Write clean, modular, and testable code
4. Performance Optimization & Simplification Analyze, improve Spark job performance and simplify complex or over engineered pipelines into standardized, efficient patterns 5. Engineering Standards & Best Practices
Your next step
Complete your application on citi.eightfold.ai. The employer’s form will show what is required.
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Already applied? Track this application
Has Citi posted this job before?
Yes. We’ve followed 3 other Senior Data Engineer jobs there since October 2026. One came down after 3 days. 2 are still up.
Large employers often post one title for several teams, so these can be separate openings.
About Citi
- People
- About 226,000 in 2025.Annual report (SEC Form 10-K)
- Company
- Listed as C.
- H-1B visas
- 1 approved for new hires in fiscal 2025.US Citizenship and Immigration Services
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 8% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
We are looking for a highly skilled Senior Data Engineer to contribute to the engineering, modernization, and continuous evolution of data processing platform on Databricks on AWS. While supporting the transition from the legacy Cloudera Hadoop platform to Databricks on AWS, this role will continue to play a key part in enhancing performance, simplifying pipelines, and delivering new capabilities on the Databricks platform over the long term.
The ideal candidate is a strong hands‑on Spark engineer with solid design experience, capable of contributing to architectural decisions while leading complex implementation and optimization efforts.
Responsibilities:
1. Platform Engineering & Modernization
Refactor and modernize existing Spark pipelines to Databricks native architectures
Eliminate legacy Hadoop dependencies and adopt cloud native AWS patterns
Enhance and extend existing processing logic using optimized Spark (ScalaSpark) on Databricks
2. Databricks Native Development
Build and optimize solutions using Databricks features, including Delta Lake, Databricks Workflows for orchestration and Auto scaling and job clusters
3. Design & Solution Engineering
Contribute to low and mid level architecture and design
Translate high level architecture into detailed technical designs
Define data models, pipeline patterns, and reusable components
Ensure solutions are scalable, maintainable, and production ready
4. Performance Optimization & Simplification
Analyze, improve Spark job performance and simplify complex or over engineered pipelines into standardized, efficient patterns
5. Engineering Standards & Best Practices
Follow and contribute to Databricks and Spark engineering standards
Write clean, modular, and testable code
Contribute to shared frameworks, reusable libraries, and quality standards
6. Collaboration & Stakeholder Engagement
Work closely with senior architects, platform teams, and DevOps engineers
Provide technical inputs, troubleshooting support, and implementation guidance
Participate in design discussions and technical decision making
7. Testing & Quality Assurance
Develop unit, integration, and data validation tests
Support production releases and post deployment validation
Qualifications:
Core Technical Skills:
8+ years in data engineering or distributed systems
Strong expertise in Apache Spark (ScalaSpark/ JavaSpark / PySpark), Databricks on AWS, and Delta Lake
Experience on SQL
Experience with AWS services and large‑scale distributed data processing
Modernization & Optimization Experience
Experience modernizing or refactoring legacy data platforms into cloud‑based architectures
Strong background in Spark performance tuning and large‑scale batch optimization
Design Capability
Ability to translate architecture into implementable designs
Understanding of data modeling and pipeline orchestration patterns
Behavioral Competencies
Strong problem‑solving mindset for complex distributed systems
Comfortable working in time‑bound, high‑impact environments
Proactive, accountable, and collaborative
Clear communication skills across global teams
Education:
Bachelor’s degree/University degree and 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.------------------------------------------------------
Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.
If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi.
View Citi’s EEO Policy Statement and the Know Your Rights poster.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Chennai, TN, IN; Pune, MH, IN
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.