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Data Engineer

Pay
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Not stated
Employment
Full-time — employment source
## Time Type: Full time \------------------------------------------------------
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting

What you’ll work on

Full posting
  • Design, develop, test and maintain PySpark and Spark batch and streaming pipelines

  • Monitor Spark streaming jobs doing eligibility and data quality checks, publishing to Kafka

  • Monitor scheduled Spark batch jobs that load audit, inbound and outbound data into Hive tables

  • Respond to ITRS alerts and job failures, kills or late triggers

  • Configure JDBC connections from SAS, Python and R to sandbox and data platform environments

From the employer’s posting
Design, develop, test, and maintain PySpark and Apache Spark data pipelines for batch and streaming workloads.
Manage and monitor Spark Streaming Jobs (running Sunday evening through Saturday afternoon) performing Eligibility and Data Quality (DQ) checks, publishing data to Kafka sender topics
Manage and monitor Spark Batch Jobs (running hourly or every 2 hours) that store audit, inbound, and outbound data into Hive tables
Respond to ITRS Alerts and system monitoring events (e.g., job failures, kills, or jobs not triggered within 30 minutes of scheduled time).
Configure and manage JDBC connections from SAS, Python, and R to dedicated Sandbox/data platform environments.
Education & alternatives
Education: * Bachelor’s degree/University degree on information technology or Engineer or equivalent experience This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
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Posting record

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Status in our records
Live
First seen by us
Oct 26, 202618 days ago
Recorded sightings
33
Last seen by us
Nov 14, 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

Time since we first saw it

Day 18

Similar jobs usually come down between day 6 and day 56.

At Citi, jobs usually come down by about day 16.

From 13,662 similar postings that came down, and 1,398 of Citi’s. Coming down is not always a hire.

Citi is hiring

303 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Data Engineer hiring is picking up
  • Takes jobs down quickly
  • 7% of open jobs were reposted
Hiring record

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.

  • Python
  • R
  • SAS
  • SQL
  • AutoSys
  • Hadoop
  • HDFS
  • Hive
  • Impala
  • Kafka
  • Oracle
  • Spark
  • PySpark
Where the posting names them
Work with large-scale data sources across Oracle, Hadoop, Impala, and SAS Server. Configure and manage JDBC connections from SAS, Python, and R to dedicated Sandbox/data platform environments. Collaborate on schema creation during code deployment; raise CMP tickets for permission grants and country-specific schema access.
Tool / Technology - Role in Platform Python / PySpark - Primary language for data pipeline development Apache Spark - Distributed compute engine for large-scale data workloads
Must Have: * Proficiency in Python and PySpark for distributed data engineering. * Experience with Apache Spark (Streaming and Batch) in production environments. * Strong understanding of SQL and ability to work with relational (Oracle) and columnar (Impala, Hive) databases. * Familiarity with Kafka or event-driven architectures. * Experience with job scheduling and monitoring tools (e.g., Autosys, ITRS). * Knowledge of data governance, access management, and information security standards. * Strong problem-solving skills for diagnosing and resolving complex data pipeline issues. Good to Have:
Respond to ITRS Alerts and system monitoring events (e.g., job failures, kills, or jobs not triggered within 30 minutes of scheduled time). Work with large-scale data sources across Oracle, Hadoop, Impala, and SAS Server. Configure and manage JDBC connections from SAS, Python, and R to dedicated Sandbox/data platform environments.
Spark Batch - Scheduled ETL jobs writing to Hive tables SAS Server - Main analytical tool with Oracle/Hadoop/Impala access Hadoop / HDFS / Hive - Distributed storage, batch processing, and table management
Good to Have: * Experience with SAS or equivalent enterprise analytical platforms. * Familiarity with SDLC practices across Development, UAT, and Production environments. ( GitHub / Light speed ) Qualifications:
Hadoop / HDFS / Hive - Distributed storage, batch processing, and table management Impala - Fast SQL querying on Hadoop data Kafka - Event streaming and messaging platform
Oracle / JDBC - Relational database connectivity Autosys - Job scheduling, alerting, and monitoring Required Skills & Qualifications
SAS Server - Main analytical tool with Oracle/Hadoop/Impala access Hadoop / HDFS / Hive - Distributed storage, batch processing, and table management Impala - Fast SQL querying on Hadoop data
Manage and monitor Spark Streaming Jobs (running Sunday evening through Saturday afternoon) performing Eligibility and Data Quality (DQ) checks, publishing data to Kafka sender topics, and processing exception/XMEV requests. Manage and monitor Spark Batch Jobs (running hourly or every 2 hours) that store audit, inbound, and outbound data into Hive tables (e.g., gfolyreg_managed.SWXPTT_audit). Respond to ITRS Alerts and system monitoring events (e.g., job failures, kills, or jobs not triggered within 30 minutes of scheduled time).
Spark Streaming - Real-time data processing and Kafka integration Spark Batch - Scheduled ETL jobs writing to Hive tables SAS Server - Main analytical tool with Oracle/Hadoop/Impala access
Design, develop, test, and maintain PySpark and Apache Spark data pipelines for batch and streaming workloads. Manage and monitor Spark Streaming Jobs (running Sunday evening through Saturday afternoon) performing Eligibility and Data Quality (DQ) checks, publishing data to Kafka sender topics, and processing exception/XMEV requests. Manage and monitor Spark Batch Jobs (running hourly or every 2 hours) that store audit, inbound, and outbound data into Hive tables (e.g., gfolyreg_managed.SWXPTT_audit).
Apache Spark - Distributed compute engine for large-scale data workloads Spark Streaming - Real-time data processing and Kafka integration Spark Batch - Scheduled ETL jobs writing to Hive tables
Impala - Fast SQL querying on Hadoop data Kafka - Event streaming and messaging platform Oracle / JDBC - Relational database connectivity
Kafka - Event streaming and messaging platform Oracle / JDBC - Relational database connectivity Autosys - Job scheduling, alerting, and monitoring
The Applications Development Programmer Analyst Citi is seeking a Applications Development Programmer Analyst 2 (C10) to join its Technology – Data Engineering function, focused on the PySpark / Spark-based Data Platform. In this role, you will design, develop, and maintain scalable data pipelines and analytical solutions, supporting large-scale data operations across enterprise systems. You will work within a full software development lifecycle (SDLC) environment spanning Development (NAM), UAT, and Production. activities.
Core Technical Duties Design, develop, test, and maintain PySpark and Apache Spark data pipelines for batch and streaming workloads. Manage and monitor Spark Streaming Jobs (running Sunday evening through Saturday afternoon) performing Eligibility and Data Quality (DQ) checks, publishing data to Kafka sender topics, and processing exception/XMEV requests.
Python / PySpark - Primary language for data pipeline development Apache Spark - Distributed compute engine for large-scale data workloads Spark Streaming - Real-time data processing and Kafka integration

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Has Citi posted this job before?

Yes. We’ve followed 3 other Data Engineer jobs there since June 2026. All 3 are still up.

  1. Jersey CityStill up after 161 days, first seen Jun 5
  2. MississaugaStill up after 79 days, first seen Aug 26
  3. PuneStill up after 26 days, first seen Oct 18
  4. This jobUp 19 days so far, first seen Oct 26

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 7% over the last 6 weeks compared with the 6 before.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of November 2. The fewest in a week was 860, the most 1,354, and the latest week had 1,335.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 6 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

View original posting ↗

The Applications Development Programmer Analyst Citi is seeking a Applications Development Programmer Analyst 2 (C10) to join its Technology – Data Engineering function, focused on the PySpark / Spark-based Data Platform. In this role, you will design, develop, and maintain scalable data pipelines and analytical solutions, supporting large-scale data operations across enterprise systems. You will work within a full software development lifecycle (SDLC) environment spanning Development (NAM), UAT, and Production. activities. Core Technical Duties Design, develop, test, and maintain PySpark and Apache Spark data pipelines for batch and streaming workloads. Manage and monitor Spark Streaming Jobs (running Sunday evening through Saturday afternoon) performing Eligibility and Data Quality (DQ) checks, publishing data to Kafka sender topics, and processing exception/XMEV requests. Manage and monitor Spark Batch Jobs (running hourly or every 2 hours) that store audit, inbound, and outbound data into Hive tables (e.g., gfolyreg_managed.SWXPTT_audit). Respond to ITRS Alerts and system monitoring events (e.g., job failures, kills, or jobs not triggered within 30 minutes of scheduled time). Work with large-scale data sources across Oracle, Hadoop, Impala, and SAS Server. Configure and manage JDBC connections from SAS, Python, and R to dedicated Sandbox/data platform environments. Collaborate on schema creation during code deployment; raise CMP tickets for permission grants and country-specific schema access. Support the retirement of legacy applications and champion adoption of modern data engineering technologies. Technical Stack Tool / Technology - Role in Platform Python / PySpark - Primary language for data pipeline development Apache Spark - Distributed compute engine for large-scale data workloads Spark Streaming - Real-time data processing and Kafka integration Spark Batch - Scheduled ETL jobs writing to Hive tables SAS Server - Main analytical tool with Oracle/Hadoop/Impala access Hadoop / HDFS / Hive - Distributed storage, batch processing, and table management Impala - Fast SQL querying on Hadoop data Kafka - Event streaming and messaging platform Oracle / JDBC - Relational database connectivity Autosys - Job scheduling, alerting, and monitoring Required Skills & Qualifications Must Have: * Proficiency in Python and PySpark for distributed data engineering. * Experience with Apache Spark (Streaming and Batch) in production environments. * Strong understanding of SQL and ability to work with relational (Oracle) and columnar (Impala, Hive) databases. * Familiarity with Kafka or event-driven architectures. * Experience with job scheduling and monitoring tools (e.g., Autosys, ITRS). * Knowledge of data governance, access management, and information security standards. * Strong problem-solving skills for diagnosing and resolving complex data pipeline issues. Good to Have: * Experience with SAS or equivalent enterprise analytical platforms. * Familiarity with SDLC practices across Development, UAT, and Production environments. ( GitHub / Light speed ) Qualifications: * 2-5 years of relevant experience * Experience in programming/debugging used in business applications * Working knowledge of industry practice and standards * Comprehensive knowledge of specific business area for application development * Working knowledge of program languages * Consistently demonstrates clear and concise written and verbal communication Education: * Bachelor’s degree/University degree on information technology or Engineer or equivalent experience This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required. \------------------------------------------------------ ## 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.
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Pune, MH, IN

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