Cloud Data Engineering Solution Architect
Employment Info
JOB DETAILS
Requirements
- Relevant tertiary qualification in information technology, computer science, data engineering, software engineering or a related discipline.
- 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.
- Desirable familiarity with engineering practices such as Python, SQL, Spark, version control, testing automation and infrastructure or pipeline-as-code.
Responsibilities
- 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.
Desired Qualifications
- Relevant certifications in cloud data architecture, data engineering, enterprise architecture or platform technologies (for example Azure, Microsoft Fabric, Databricks or TOGAF) are desirable.
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