Role Overview
The Data Architect is responsible for designing, implementing, and governing the organisation’s data architecture across SQL, NoSQL and modern analytics platforms, with a particular focus on Databricks. You will define end‑to‑end data solutions that support AI Coach analytics and AI/ML use cases, ensuring scalability, performance, security, and data quality.
Key Responsibilities
- Work with existing Insight Databricks team to design and own the enterprise data architecture, including data models, integration patterns and data flows across the AI Coach applications data layer.
- Design relational data models (OLTP and OLAP) for SQL platforms (e.g. SQL Server, PostgreSQL, Azure SQL etc.).
- Design schemas and data models for NoSQL stores (e.g. Cosmos DB, MongoDB, Cassandra, DynamoDB) aligned to access patterns and scalability needs.
- Define standards for data ingestion, transformation, storage, cataloguing, and consumption.
- Architect and guide the implementation of ELT/ETL pipelines in Databricks (PySpark/SQL), including streaming and batch workloads.
- Optimise Databricks clusters, jobs, and workflows for cost, performance, and reliability.
- Implement data governance, quality, and lineage in Databricks using Unity Catalog (or equivalent tools).
- Partner with data engineers to ensure best practices in code structure, testing, CI/CD, and deployment.
Data Governance, Quality & Security
- Define and enforce data standards, naming conventions, and modelling best practices.
- Define and support data quality rules, monitoring, and remediation processes.
Stakeholder Engagement & Strategy
- Collaborate with business stakeholders, product owners and analysts to translate requirements into scalable data solutions.
- Contribute to the data strategy, roadmap and architecture principles to support analytics, BI, and AI/ML initiatives.
Required Skills & Experience
Technical Skills
- Strong experience as a Data Architect, Senior Data Engineer, or similar role in data-intensive environments.
- Advanced SQL skills, including complex queries, stored procedures, query tuning, and performance optimisation.
- Hands-on experience with at least one major relational database platform (e.g. SQL Server, PostgreSQL, Oracle, MySQL, Azure SQL).
- Hands-on experience designing and implementing solutions with at least one major NoSQL technology (e.g. MongoDB, Cosmos DB).
Soft Skills
- Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Strong problem-solving and analytical skills; comfortable dealing with ambiguity.
- Collaborative mindset and experience working in cross-functional way with the rest of the AI Coach development team.
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