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Lead Data Engineer – Spark / Scala - Vice President

Belfast, Northern Ireland, GB

Actively hiring, first seen by us today
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Full-time — employment source
## Time Type: Full time \------------------------------------------------------
Employment type in the employer’s posting: FULL_TIME
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Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Nov 9, 2026today
Recorded sightings
1

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How this job compares

Time since we first saw it

Day 0

Early. Similar jobs usually come down between day 5 and day 54.

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

From 12,066 similar postings that came down, and 1,288 of Citi’s. Coming down is not always a hire.

Citi is hiring

168 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
Hiring record

See how this role fits your experience

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  • Java
  • Scala
  • AWS
  • Databricks
  • Delta Lake
  • Hadoop
  • Kafka
  • S3
  • Spark
  • Airflow
  • PySpark
Where the posting names them
Key Skills and Experience: * Experience with Scala Spark or PySpark or Java Spark — comfort working across multiple Spark language APIs * Familiarity with AWS services such as S3, Glue, IAM, CloudWatch, or Step Functions in a data engineering context * Exposure to data reconciliation or financial data domains — understanding of recon logic, data validation, and accuracy requirements at scale * Experience with CI/CD pipelines and DevOps practices — automated testing, deployment pipelines, and version control in a data engineering context * Knowledge of data modelling concepts and pipeline orchestration patterns beyond Databricks Workflows (e.g. Apache Airflow) * Prior experience working in large-scale Hadoop to cloud migration programmes or legacy platform modernisation projects * Familiarity with streaming data processing (e.g. Apache Kafka, Spark Structured Streaming) alongside batch workloads * Experience contributing to shared engineering frameworks or reusable libraries within a platform team setting What we’ll provide you:
What We Do: Our team owns and drives a large-scale reconciliation data platform built on Scala Spark. We are currently on an ambitious journey to migrate and modernize our platform from a legacy Cloudera Hadoop environment to Databricks on AWS — adopting cloud-native patterns, simplifying pipelines, and unlocking new capabilities along the way. The work is technically complex, high-impact, and directly tied to data quality outcomes that matter across the organization. Where We Fit:
What Makes Our Team Interesting: * We are working on a high-impact, technically challenging modernization — moving a production-grade reconciliation platform from Hadoop to Databricks on AWS * The domain — data reconciliation at scale — is inherently complex and intellectually rewarding, involving large datasets, performance-critical pipelines, and precision engineering * We value strong individual contributors — this is a hands-on role where your Scala Spark expertise will directly shape the platform's future * We are a team that is enthusiastic about what we are building — there is a genuine drive to do things the right way, adopt modern patterns, and continuously raise the bar on engineering quality * You will have the opportunity to contribute to architectural decisions, not just execute them Role Overview/What will you do:
Role Overview/What will you do: * Build and optimise large-scale Scala Spark data pipelines on Databricks, focusing on the reconciliation domain — writing clean, modular, and production-ready code * Drive modernisation efforts by refactoring legacy Hadoop-based pipelines into cloud-native Databricks/AWS architectures using Delta Lake and Databricks Workflows * Tune and simplify complex or over-engineered Spark jobs — analysing performance bottlenecks and transforming them into efficient, standardised patterns * Translate designs into reality — take high-level architectural decisions and convert them into detailed technical implementations, data models, and reusable pipeline components * Collaborate daily with architects, platform, and DevOps teams on design discussions, technical decisions, and production releases * Write and maintain tests — unit, integration, and data validation — to ensure quality and reliability of reconciliation pipelines * Contribute to engineering standards — shared frameworks, reusable libraries, and best practices across the data platform This role exists to strengthen and evolve a business-critical data reconciliation platform — ensuring it is scalable, performant, and future-ready. The individual will be a key hands-on contributor driving the platform's migration from legacy Hadoop to Databricks on AWS, while continuously improving the quality and efficiency of reconciliation data processing at scale.
On a day-to-day basis, the team collaborates closely with: * Senior Architects & Platform Teams – to shape technical direction and design decisions * DevOps & Cloud Engineers – to support infrastructure, deployments, and cloud-native adoption on AWS * Stakeholders & Business Teams – to understand reconciliation requirements and translate them into scalable engineering solutions What Makes Our Team Interesting:
* Build and optimise large-scale Scala Spark data pipelines on Databricks, focusing on the reconciliation domain — writing clean, modular, and production-ready code * Drive modernisation efforts by refactoring legacy Hadoop-based pipelines into cloud-native Databricks/AWS architectures using Delta Lake and Databricks Workflows * Tune and simplify complex or over-engineered Spark jobs — analysing performance bottlenecks and transforming them into efficient, standardised patterns * Translate designs into reality — take high-level architectural decisions and convert them into detailed technical implementations, data models, and reusable pipeline components * Collaborate daily with architects, platform, and DevOps teams on design discussions, technical decisions, and production releases * Write and maintain tests — unit, integration, and data validation — to ensure quality and reliability of reconciliation pipelines * Contribute to engineering standards — shared frameworks, reusable libraries, and best practices across the data platform This role exists to strengthen and evolve a business-critical data reconciliation platform — ensuring it is scalable, performant, and future-ready. The individual will be a key hands-on contributor driving the platform's migration from legacy Hadoop to Databricks on AWS, while continuously improving the quality and efficiency of reconciliation data processing at scale. This is a global, cross-functional role with day-to-day interaction across:
This is a global, cross-functional role with day-to-day interaction across: * Global engineering and architecture teams — collaborating on platform design, standards, and technical direction * DevOps and cloud infrastructure teams — supporting deployments and cloud-native adoption on AWS * Regional and local stakeholder teams — engaging with business and data operations colleagues who rely on the reconciliation outputs Key Skills and Experience:

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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.

Weekly new Data Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 834, the most 1,312, and the latest week had 1,079.
August 17Last week

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

View original posting ↗

Engineer the future of global finance. At Citi, our Tech team doesn’t just support finance – we are helping to redefine it. Every day, $5 trillion crosses through our network. We do business in 180+ countries operating at a scale few can match. From deploying advanced AI to helping shape global markets, we build systems that matter. Look to join a team where your work helps influence economies, your ideas can drive innovation and outcomes, and your growth is backed by mentorship, continuous learning and flexibility with potential hybrid work opportunities. Help solve real-world challenges that touch millions and get the opportunity to build the future of finance with Citi Tech. About the Team: We are an established data engineering team with a strong focus on reconciliation — building and maintaining large-scale data reconciliation platforms that ensure accuracy, consistency, and integrity across critical financial data. This is not a new team; we have a solid foundation and a proven track record, and we are now entering an exciting phase of modernization and evolution. What We Do: Our team owns and drives a large-scale reconciliation data platform built on Scala Spark. We are currently on an ambitious journey to migrate and modernize our platform from a legacy Cloudera Hadoop environment to Databricks on AWS — adopting cloud-native patterns, simplifying pipelines, and unlocking new capabilities along the way. The work is technically complex, high-impact, and directly tied to data quality outcomes that matter across the organization. Where We Fit: Within the broader organization, our team sits at the intersection of data engineering and financial data operations — playing a critical role in ensuring that large volumes of data are processed, validated, and reconciled accurately and at scale. The reliability of our platform has a direct impact on downstream reporting, risk, and decision-making. Who We Work With On a day-to-day basis, the team collaborates closely with: * Senior Architects & Platform Teams – to shape technical direction and design decisions * DevOps & Cloud Engineers – to support infrastructure, deployments, and cloud-native adoption on AWS * Stakeholders & Business Teams – to understand reconciliation requirements and translate them into scalable engineering solutions What Makes Our Team Interesting: * We are working on a high-impact, technically challenging modernization — moving a production-grade reconciliation platform from Hadoop to Databricks on AWS * The domain — data reconciliation at scale — is inherently complex and intellectually rewarding, involving large datasets, performance-critical pipelines, and precision engineering * We value strong individual contributors — this is a hands-on role where your Scala Spark expertise will directly shape the platform's future * We are a team that is enthusiastic about what we are building — there is a genuine drive to do things the right way, adopt modern patterns, and continuously raise the bar on engineering quality * You will have the opportunity to contribute to architectural decisions, not just execute them Role Overview/What will you do: * Build and optimise large-scale Scala Spark data pipelines on Databricks, focusing on the reconciliation domain — writing clean, modular, and production-ready code * Drive modernisation efforts by refactoring legacy Hadoop-based pipelines into cloud-native Databricks/AWS architectures using Delta Lake and Databricks Workflows * Tune and simplify complex or over-engineered Spark jobs — analysing performance bottlenecks and transforming them into efficient, standardised patterns * Translate designs into reality — take high-level architectural decisions and convert them into detailed technical implementations, data models, and reusable pipeline components * Collaborate daily with architects, platform, and DevOps teams on design discussions, technical decisions, and production releases * Write and maintain tests — unit, integration, and data validation — to ensure quality and reliability of reconciliation pipelines * Contribute to engineering standards — shared frameworks, reusable libraries, and best practices across the data platform This role exists to strengthen and evolve a business-critical data reconciliation platform — ensuring it is scalable, performant, and future-ready. The individual will be a key hands-on contributor driving the platform's migration from legacy Hadoop to Databricks on AWS, while continuously improving the quality and efficiency of reconciliation data processing at scale. This is a global, cross-functional role with day-to-day interaction across: * Global engineering and architecture teams — collaborating on platform design, standards, and technical direction * DevOps and cloud infrastructure teams — supporting deployments and cloud-native adoption on AWS * Regional and local stakeholder teams — engaging with business and data operations colleagues who rely on the reconciliation outputs Key Skills and Experience: * Experience with Scala Spark or PySpark or Java Spark — comfort working across multiple Spark language APIs * Familiarity with AWS services such as S3, Glue, IAM, CloudWatch, or Step Functions in a data engineering context * Exposure to data reconciliation or financial data domains — understanding of recon logic, data validation, and accuracy requirements at scale * Experience with CI/CD pipelines and DevOps practices — automated testing, deployment pipelines, and version control in a data engineering context * Knowledge of data modelling concepts and pipeline orchestration patterns beyond Databricks Workflows (e.g. Apache Airflow) * Prior experience working in large-scale Hadoop to cloud migration programmes or legacy platform modernisation projects * Familiarity with streaming data processing (e.g. Apache Kafka, Spark Structured Streaming) alongside batch workloads * Experience contributing to shared engineering frameworks or reusable libraries within a platform team setting What we’ll provide you: By joining Citi, you will not only be part of a business casual workplace with a hybrid working model (up to 2 days working at home per week), but also receive a competitive base salary (which is annually reviewed), and enjoy a whole host of additional benefits such as: * 27 days annual leave (plus bank holidays) * A discretional annual performance related bonus * Private Medical Care & Life Insurance * Employee Assistance Program * Pension Plan * Paid Parental Leave * Special discounts for employees, family, and friends * Access to an array of learning and development resources Visit our About Us | Culture, Values & Benefits page to learn more. Alongside these benefits Citi is committed to ensuring our workplace is where everyone feels comfortable coming to work as their whole self, every day. We want the best talent around the world to be energized to join us, motivated to stay and empowered to thrive. #LI-BH2 \------------------------------------------------------ ## 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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Belfast, Northern Ireland, GB

Engineer the future of global finance. At Citi, our Tech team doesn’t just support finance – we are helping to redefine it. Every day, $5 trillion crosses through our network. We do business in 180+ countries operating at a scale few can match. From deploying advanced AI to helping shape global markets, we build systems that matter. Look to join a team where your work helps influence economies, your ideas can drive innovation and outcomes, and your growth is backed by mentorship, continuous learning and flexibility with potential hybrid work opportunities. Help solve real-world challenges that touch millions and get the opportunity to build the future of finance with Citi Tech. About the Team:
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What we’ll provide you: By joining Citi, you will not only be part of a business casual workplace with a hybrid working model (up to 2 days working at home per week), but also receive a competitive base salary (which is annually reviewed), and enjoy a whole host of additional benefits such as: * 27 days annual leave (plus bank holidays) * A discretional annual performance related bonus * Private Medical Care & Life Insurance * Employee Assistance Program * Pension Plan * Paid Parental Leave * Special discounts for employees, family, and friends * Access to an array of learning and development resources
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