Cloud Data Engineering Solution Architect
Job Description
Job Description
The Data Engineering Solution Architect plays a critical role in shaping and governing TAL’s modern data ecosystem, defining solution design standards, engineering patterns, and technical frameworks that enable the delivery of secure, scalable and trusted data capabilities. This position translates business, analytics and platform requirements into end-to-end data solutions, covering ingestion, transformation, storage, orchestration and lifecycle management, while leveraging cloud-native technologies and modern engineering practices.
Working across Technology, Data, Cyber, Risk and business teams, the Architect ensures data solutions align with enterprise architecture, governance and risk standards, while remaining practical and fit for purpose. Through strong stakeholder engagement and influence, the role partners with engineers, product owners and delivery teams to modernise legacy environments, enhance interoperability, and build reusable data capabilities that support reporting, analytics, operational insights and emerging AI use cases.
In this role you will:
- Define and evolve TAL’s data engineering architecture, standards and reference patterns across ingestion, storage, processing, orchestration and consumption.
- Define and maintain engineering standards for batch and real-time data movement, transformation, orchestration, observability, metadata capture and pipeline resilience.
- Lead the architectural design of TAL’s cloud-based data platform capabilities across Azure and Microsoft Fabric supporting integration services, selecting the right patterns for each use case.
- Embed governance, lineage, data quality, classification, privacy and access control requirements into architecture patterns and solution designs from the outset.
- Provide hands-on architectural guidance to delivery teams, supporting solution shaping, design assurance, estimation and technical decision-making across data initiatives.
- Build strong partnerships across Technology, business domains, Data, Risk, Cyber and strategic partners to ensure architecture decisions reflect enterprise priorities and delivery realities.
Qualifications
- Relevant tertiary qualification in information technology, computer science, data engineering, software engineering or a related discipline.
- Relevant certifications in cloud data architecture, data engineering, enterprise architecture or platform technologies (for example Azure, Microsoft Fabric, Databricks or TOGAF) are desirable.
- Strong understanding of modern data architecture patterns, including lakehouse and warehouse architectures, medallion or layered data design, batch and streaming ingestion, and data serving patterns.
- Deep knowledge of cloud-native data services and tooling, particularly Azure data services, Microsoft Fabric, Databricks, SQL-based platforms and integration technologies.
- Knowledge of data modelling, metadata management, lineage, data quality, observability, orchestration, CI/CD and platform automation practices relevant to enterprise data engineering.
- Broad understanding of data governance, privacy, security, resilience, risk and audit requirements relevant to enterprise data platforms.
- Understanding of how data platforms enable self-service analytics, data products, semantic access, operational reporting and AI/ML lifecycle needs.
- Familiarity with engineering practices such as Python, SQL, Spark, version control, testing automation and infrastructure or pipeline-as-code is desirable.
Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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