SQL Developer / Core Banking Data Engineer
We’re looking for a Core Banking Data Engineer to design, build, and operate the data foundations that power a modern, cloud-native core banking platform.
The role focuses on high-integrity financial data pipelines, event streaming, ledger/transaction data modelling, regulatory-grade controls, and analytics-ready datasets that serve Finance, Risk, Operations, Product, and Regulatory reporting.
You will partner closely with Core Banking Product Engineers, Platform Engineers, Security/Risk, and Data Consumers (Finance, Treasury, Risk, BI, and Compliance) to ensure data is accurate, auditable, reconciled, and observable—with strong discipline around ledger integrity, idempotency, data lineage, and operational resilience.
This role suits candidates with experience delivering data platforms in regulated environments—ideally with exposure to modern core banking/ledger platforms (e.g., Thought Machine Vault, 10x ) and/or high-throughput financial transaction systems.
1. Accountabilities and Responsibilities
Core Banking Data Engineering (Ledger & Transaction Data)
Design and implement data ingestion and transformation for core banking domains: accounts, balances, transactions, postings, interest, fees, limits, arrears/delinquency, lifecycle events, and product parameters.
Build data structures that support double-entry ledger concepts, including posting sets, journals, sub-ledgers, balances (available/cleared), and reconciliation between operational and reporting views.
Implement robust idempotent ingestion patterns to safely process retries and prevent duplication (critical for event-driven banking data).
Create canonical domain models and “golden sources” for key entities (customer, account, transaction, product, ledger entry).
Streaming, Integrations & Data Movement
Build and maintain event-driven pipelines (e.g., Kafka or equivalent) from core banking and surrounding systems (payments, cards, KYC, fraud, CRM, notifications).
Develop batch and streaming processing patterns (CDC, micro-batching, pub/sub) with strong error handling, replay, dead-lettering, and backfill strategies.
Implement integration patterns that support near-real-time needs (alerts, operational monitoring, fraud/AML signals) and end-of-day needs (GL extracts, regulatory reports).
Data Platform & Operability (Production Excellence)
Build and operate scalable data infrastructure in cloud environments (AWS/Azure/GCP), including orchestration, compute, storage, and metadata management.
Implement observability for data pipelines: logs, metrics, tracing, pipeline SLOs/SLIs, runbooks, and operational dashboards.
Participate in incident response and root-cause analysis; improve resilience through automation, testing, and post-incident actions.
Delivery, Documentation & Collaboration
Work with Product Owners, Finance, Risk and Operations SMEs to translate requirements into data products (curated datasets, marts, extracts, APIs).
Produce clear technical documentation: data contracts, schemas, lineage diagrams, decision records, reconciliation playbooks, and operating procedures.
Contribute reusable components and engineering standards: common ingestion frameworks, validation libraries, schema evolution patterns, and deployment templates.
Data Quality, Controls & Reconciliation (Regulatory-grade)
Define and enforce data quality rules (completeness, validity, timeliness, uniqueness) with automated monitoring and alerting.
Design reconciliation controls to validate that reporting datasets reconcile to source systems (e.g., totals by currency, posting sums, balancing checks, control totals, trial-balance alignment).
Ensure datasets support audit requirements: lineage, traceability, immutability where appropriate, and clear “explainability” from report numbers back to raw events.
Implement privacy-by-design (GDPR) and retention controls (masking, tokenization, encryption, purge workflows).
2. Experience and Key Competencies:
Knowledge & Experience:
5+ years building and operating data pipelines in regulated enterprise environments; banking/financial services experience strongly preferred.
Strong experience designing data solutions for transactional/financial systems with emphasis on accuracy, auditability, and reconciliation.
Practical knowledge of ledger and accounting concepts (double-entry, postings, balances, control totals, sub-ledger vs GL).
Experience with data modelling (dimensional and/or domain-driven), handling slowly changing dimensions, and designing analytics-ready datasets.
Familiarity with core banking data domains and adjacent systems: payments (SEPA/SWIFT/Faster Payments), cards, KYC/AML, onboarding, fraud/monitoring, and customer servicing workflows.
Experience supporting regulatory reporting and operational reporting with strong governance controls (e.g., lineage, approvals, evidence packs, audit trails).
Engineering Fundamentals (Required)
Strong programming in one or more - Python, Java, Scala, Kotlin, Go (or similar).
Strong SQL skills and experience tuning complex transformations.
Experience with streaming/event platforms (Kafka or equivalent) and schema management (schema registry patterns, schema evolution).
Experience with CI/CD, version control (Git), automated testing, and Infrastructure-as-Code practices.
Data Platform Tooling (Typical, not exhaustive)
Cloud data services and patterns: object storage, managed compute, secret management, key management, IAM.
Data warehouse/lakehouse experience (e.g., Snowflake, BigQuery, Synapse, Databricks) and ELT/ETL tools/orchestrators (e.g., Airflow, Dagster, Azure Data Factory).
Metadata, lineage and governance tooling exposure is a plus (catalogs, data contracts, policy-as-code).
Cloud & Operability
Experience in cloud-native environments and production support with an SRE mindset.
Familiar with observability: monitoring, alerting, error budgets/SLOs, and operational readiness reviews.
Strong problem-solving and disciplined incident response skills.
Soft Skills
Strong stakeholder management and ability to translate business needs into data products and quality controls.
Excellent written documentation skills, with a commitment to clarity and maintainability.
Ability to work effectively in ambiguous environments, managing multiple priorities with minimal oversight
Personal Attributes
Highly organised, proactive, and detail‑oriented, with the ability to operate at pace.
Comfortable operating in ambiguity and adapting to changing priorities.
Resilient, calm under pressure, and confident acting as an extension of the CIO.
Trusted partner with a collaborative, inclusive leadership style.
Key Competencies:
Communications & Relationships:
Excellent communication skills required to manage third party relationships. Ability to use insights and relationships to influence and deliver. The ability to build connections and partnerships within own business area and beyond, through formal and informal channels, utilising considerable tact, diplomacy and people skills.
Agility and innovation:
Collaboration:
Drive for results:
Ethics and trust:
Inclusion:
Customer centricity:
Commercial Judgement:
Managing Programs:
Proven analytical, decision-making and problem-solving skills, with the ability to plan and implement appropriate measures to mitigate the impact of an event affecting USBE’s ability to achieve its objectives. To complete day-to-day activities in a manner which is consistent with legal, regulatory and stakeholder expectations.
3 Conduct Standards & Rules
You must act with professionalism and integrity
You must act with due skill and diligence
You must be open and cooperative with the Central Bank of Ireland and other regulators
You must disclose appropriately any information of which the Central Bank of Ireland would reasonably expect notice
Location expectations
This role requires working from a U.S. Bank location three (3) or more days per week.
