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 —…