Why This Role Stands Out
Embark on a career-defining journey as a Senior Data Engineer, shaping the future of AI-native banking by designing and building robust data migration pipelines. You'll thrive in this role if you're a skilled engineer passionate about complex data challenges and eager to contribute to a company revolutionizing the financial industry, with the flexibility of a hybrid work environment. Join Matchbox and build reusable, scalable data tooling that directly impacts the success of major banking transformations.
Quick Overview
Job Description
Constantinople delivers a new era of AI-native banking. Constantinople provides banks with a fully-managed software and AI operational platform, which brings together customer experience, product, data, operations, compliance and infrastructure in a single platform.
Constantinople's AI-native platform eliminates the need for expensive infrastructure, and replaces manual operational and compliance processes with AI at scale. By removing the operational complexity of banking, Constantinople enables our client banks to focus on their customers and thebusinessof banking.
What You'll Do- Design and build end-to-end data migration pipelines that extract, transform, and load core banking data from legacy systems with a strong focus on Ultradata source environments into Constantinople's platform
- Develop and maintain transformation logic and data mapping frameworks that accurately translate legacy banking data models, business rules, and product configurations into Constantinople's schema
- Build robust data validation, reconciliation, and integrity checking frameworks to ensure every migration lands with full accuracy and auditability
- Own the design and development of Constantinople's core migration data tooling, creating reusable frameworks that scale across multiple client onboardings
- Work with Snowflake as the primary analytical and staging environment building pipelines, models, and data products that support both migration execution and post-migration reporting
- Collaborate with Technical BAs to turn data mapping specifications and business rules into production-grade migration code
- Support migration dry runs, parallel runs, and live cutovers including rapid triage and resolution of data issues under time pressure
- Partner with platform engineers and solutions engineering to ensure migrated data integrates cleanly with downstream systems, APIs, and banking operations
- Build cutting-edge tools and frameworks that convert raw legacy banking data into clean, validated, and operationally ready assets on the Constantinople platform
- Champion clean, maintainable, and well-documented code and data architecture that the whole team can build on
- 5+ years of data engineering experience, with hands on involvement in large-scale data migrations ideally within banking, fintech, or financial services
- Direct experience with Ultradata (the core banking platform) understanding its data model, schema structure, and export formats is highly desirable and will set your application apart
- Proficient with Snowflake including pipeline development, data modelling, dbt transformations, and performance optimisation in a Snowflake environment
- Strong proficiency in Python and SQL, with a track record of building production-grade data pipelines
- Solid understanding of relational and NoSQL databases, including schema design, query optimisation, and data integrity patterns
- Experience with modern data stack tooling dbt, Spark/Flink, columnar data formats, and workflow orchestration (Airflow/MWAA)
- Familiarity with AWS data services: S3, Athena, Glue, EKS, MWAA experience with the full AWS data stack is preferred
- A precision mindset you understand that in financial data migration, correctness is non negotiable and edge cases are the job, not the exception
- Strong data intuition with the ability to translate complex business rules and legacy data structures into scalable engineering solutions
- Collaborative by nature comfortable working across engineering, delivery, and client facing teams, and able to communicate technical constraints clearly to non technical stakeholders
- Comfortable with the pace and ambiguity of a high growth startup, and energised by building capability from the ground up
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