Senior Data Engineer, Core Banking Migrations

Constantinople

Senior Data Engineer designing and building data migration pipelines for banks at Constantinople. Ensure accurate data transformation and compliance within a modern data environment.

Posted 7/14/2026full-timeSydney • 🇦🇺 AustraliaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and building end-to-end data migration pipelines, with a strong focus on Ultradata and Snowflake environments. Proficient in Python, SQL, and modern data stack tooling, ensuring data integrity and accuracy throughout the migration process.

Highest-signal resume keywords

Data Engineering ExperienceUltradata ExpertiseSnowflake ProficiencyPython and SQL SkillsData Migration Framework Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data MigrationData MappingData ValidationData IntegrityPipeline DevelopmentSQLPythonSchema DesignNoSQL DatabasesWorkflow Orchestration

Soft Skills

CollaborationCommunicationProblem-SolvingAttention to DetailAdaptability

Tools & Technologies

SnowflakeUltradataDbtSparkFlinkAirflowAWS S3AWS AthenaAWS GlueAWS EKS

Industry Keywords

BankingFintechFinancial ServicesData MigrationData Engineering

Tech Stack

Tools & technologies

AirflowAWSNoSQLPythonSparkSQL

About the role

Key responsibilities & impact

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

Requirements

What you’ll need

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

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Constantinople Website LinkedIn All Job Openings 51 - 200 employees Constantinople is the first of its kind: an all-in-one software and operational platform for banks. We host and manage your bank’s customers directly on our cloud-native infrastructure. We support a full-suite of banking products which are branded as your own, together with all operational services needed to run your bank. Senior Data Engineer, Core Banking Migrations Job not on LinkedIn 🔥 43 minutes ago 🏢🏡 Sydney – Hybrid ⏰ Full Time 🟠 Senior 🚰 Data Engineer Airflow AWS NoSQL Python Spark SQL Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
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 🎯 Requirements
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
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