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Belfast, Northern Ireland, GB
Actively hiring, first seen by us today## Time Type: Full time \------------------------------------------------------
Employment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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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.
168 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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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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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.
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.
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.
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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:
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
No clear work-authorization passage found. Eligibility is unconfirmed.