Develop conceptual and logical data architectures for specific domains, squads, or projects, adapting enterprise frameworks to local needs while ensuring alignment with governance standards and regulatory obligations.
Integrate data quality metrics, lineage tracking, metadata standards, and privacy/security controls into data architectures, ensuring that solutions can reliably support risk data aggregation and timely reporting as mandated by international banking guidelines.
Work closely with Data Modellers, providing detailed architectural artifacts (architecture artefacts, diagrams, data flows) to guide the creation of logical and physical data models.
Collaborate with Data Engineers, Data Governance teams, and other stakeholders to clarify architectural intent, resolve technical challenges, and ensure that resulting data solutions are both compliant and optimised for performance, scalability, and cost efficiency.
Take part in proofs of concept (POCs), pilot projects, and sandbox initiatives to test and refine architectural approaches, ensuring flexibility and adaptability to evolving risk reporting requirements and emerging technologies.
Identify opportunities to improve domain-level architectures based on feedback from squads, changes in regulatory landscapes, advancements in analytics tools, or shifting business priorities.
Requirements
Bachelor’s degree in Computer Science, Informatics, Information Systems, or a related field
Minimum of 6–8 years experience in data architecture, data warehousing, cloud-based BI solutions, and an understanding of data governance and regulatory frameworks in a banking or similarly regulated environment.
Demonstrated ability to balance technical optimisation with governance and compliance imperatives, ensuring data lineage, quality, and security are integral to architectural designs.
Strong communication, problem-solving, and collaborative skills to work effectively with technical teams, governance stakeholders, and business units.
Competencies & Skills: Data Architecture & Modelling Techniques (Conceptual/Logical)
Alignment with Governance, Data Quality, and Regulatory Standards
Senior Associate Data Engineer contributing to Travelers' analytics landscape by building and operationalizing data solutions. Collaborating with teams to ensure reliable data delivery across the enterprise.
Salesforce Data Engineer serving as a subject matter expert in the State of Tennessee. Designing scalable data pipelines and collaborating on cross - agency initiatives.
Data Engineer Senior responsible for building data architecture and optimizing pipelines for Business Intelligence. Collaborating with analysts to develop insights using Power BI and Azure technologies.
Principal Data Engineer driving modernization from legacy systems to cloud - native platforms at Mastercard. Architecting and developing ETL platforms with AI integration and establishing data - driven strategies.
Principal Data Engineer modernizing cloud - native platforms for AI - powered solutions at Mastercard. Leading teams to enhance data processing efficiency and reliability across global operations.
Data Engineer creating data pipelines for Santander's card transactions. Collaborating with an agile team in strategic projects involving Databricks and PySpark.
Data Engineer designing, implementing, and maintaining data pipelines at Sabiá Gaming. Focused on high - quality data access and integration for enhanced decision - making.
Quantitative Data Engineer developing data solutions and automations for MassMutual's investment management. Working with data orchestration tools within a collaborative team environment.
Senior Data Engineer designing and scaling data infrastructure for analytics, machine learning, and business intelligence in a software supply chain security company.