Data Architect
Indexed description
The ideal candidate combines deep and extensive technical and architectural expertise with strong understanding of business processes, vendor management, and program leadership.
Responsibilities
- Develop a deep understanding of the existing data landscape (DWH & models, ETL process, Power BI semantic models & datasets), its architectural gaps, scalability constraints, and data quality risks.
- Lead the evaluation, selection, and implementation of a cloud-based data platform.
- Manage external implementation partners and consulting teams. Own technical, commercial, and architectural decision making.
- Monitor project scope, budget, timelines, risks, dependencies, and deliverables.
- Optimize cloud infrastructure, storage, and operational costs and maintain performance and scalability.
- 5+ years of the following
- SQL – advanced SQL and relational database expertise including SSIS, stored procedures, views
- ETL/ELT – experience with building and orchestrating pipelines and frameworks
- Architecture – proven experience with cloud data warehousing, data lakes, and lakehouse architecture
- Data modelling – proven ability to translate complex business processes into conceptual, logical, physical, dimensional, and semantic data models designed for BI/AI consumption
- Power BI – hands on expertise with DAX and performance optimization
- Data Governance – extensive knowledge of metadata management, data quality, and lineage Cloud Data Platforms (Snowflake, Microsoft Fabric, AWS RDS) – experience managing performance, storage, compute and cost optimization
- ERP Systems – Priority ERP including REST API / OData integration and data extraction patterns
- Collaboration tools — Microsoft Teams, Atlassian Jira, GitHub.
- AI-assisted development – experience working with LLMs, prompt engineering, or Claude Code – advantage.
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