Lead Data Architect

Tasks

About the role

Our data estate combines modern cloud platforms (Snowflake, Databricks, Microsoft Fabric on Azure, Power BI) with on-prem SQL Server databases we are modernizing. Each platform has an expert domain architect. What we need now is the architect who makes them work together as one coherent, AI-ready ecosystem.
As Lead Data Architect, you will shape our warehouse and lakehouse architecture, data models, pipelines and standards, aligned to the Hydro Data Strategy. You will lead through expertise, judgement and trust rather than hierarchy, with a clear mandate for cross-platform decisions.

What you will be doing

• Architect and optimize warehouse and lakehouse solutions on Snowflake, Databricks and Azure, integrated with on-prem databases, for analytical, regulatory and operational workloads
• Lead conceptual, logical and physical data modelling standards, using dimensional and data vault methods, and champion canonical models and metadata standards for data product reuse
• Work with BI and Analytics teams to define semantic and business layers that enable self-service analytics
• Define patterns for ingestion, pipelines, orchestration and automation, and set pragmatic standards for CI/CD, infrastructure as code, testing and observability
• Make our data environments AI/ML-ready, working with data scientists and ML engineers on feature data, versioning, reproducibility and provisioning for training and inference
• Define and enforce D&A architecture standards through proportionate design reviews, so solutions meet security, regulatory and Enterprise Architecture requirements
• Help teams decide when to use our standard technologies and when a new path is justified, and advise on prioritizing updates to existing systems
• Lead by example in design sessions, mentor architects and engineers, and keep teams informed of relevant architecture trends

How decisions work

Domain architects decide within their platforms. You decide on cross-platform patterns and D&A modelling standards within an agreed mandate. Enterprise-wide standards, exceptions and technology adoption follow Enterprise Architecture governance and the D&A Manager. Data strategy, policy and business definitions sit with Data Governance. You will be expected to recommend clearly and escalate well.

Requirements

• 10+ years in data engineering, data warehousing or data platforms, including 4+ years as an architect or principal engineer
• Deep expertise in warehouse and lakehouse architecture on modern cloud platforms (at least two of Snowflake, Databricks, Microsoft Fabric)
• Strong data modelling: conceptual, logical and physical; dimensional and data vault; canonical models and semantic layers
• SQL Server architecture and performance expertise, and experience modernizing on-prem estates to the cloud