Data Architect - Databricks
6 month contract
Dublin - Hybrid
€- per day
The Role
Data Architect required to lead the evolution of our enterprise data platform infrastructure and engineering frameworks. This role will
be a key technical leader, working cross-functionally with data engineers, software developers, product teams, and enterprise architects to ensure the platform supports current and future data-driven initiatives & will be instrumental in shaping the architecture of our Azure-based data ecosystem, driving AI enablement, and ensuring scalable, secure, and high-performance data solutions across the organisation.
Principal Responsibilities
1. Architectural Leadership: Lead the selection and implementation of data infrastructure technologies, such as data lakes, warehouses, lakehouses, orchestration tools, and streaming platforms.
2. Design and evolve the enterprise data architecture, including integration with Databricks, Data Lake, Data Factory, and other core services.
3. AI Enablement: Collaborate with Data Science and AI teams to architect solutions that support machine learning operations (MLOps), predictive analytics, and intelligent automation.
4. Platform Strategy: Define & implement engineering standards, best practices, governance frameworks, and architectural blueprints for the data platform ecosystem.
5. Stakeholder Engagement: Partner with business units, product owners, and engineering teams to translate strategic goals into scalable data solutions.
6. Innovation & Optimisation: Evaluate emerging technologies and recommend enhancements to improve performance, cost-efficiency, and resilience of the data platform.
7. Security & Compliance: Ensure data architecture adheres to compliance standards, including GDPR and EEA residency requirements.
8. Enterprise Scale: Work with Enterprise DevOps and Cloud Engineering teams to ensure infrastructure-as-code, CI/CD, and monitoring practices are in place.
9. Mentorship: Guide and upskill data engineers and analysts in best practices for data architecture, pipeline design, and cloud-native development.
Knowledge, Qualifications, Experience & Skills
Skills & Experience
• Proven experience architecting data platforms on Microsoft Azure, including Databricks, Data Lake Storage Gen2 & Azure Data Factory.
• Strong understanding of Lakehouse architecture, Delta Lake, PySpark & SQL.
• Experience with AI/ML workflows, including MLOps, model lifecycle management, and integration with data pipelines.
• Strong understanding of data governance, lineage, security, and privacy frameworks.
• Proficiency in data modelling, ETL/ELT design, and metadata management.
• Familiarity with Power BI, Azure DevOps or Jira, GitHub and CI/CD pipelines.
• Experience in large-scale enterprise environments with complex data ecosystems.
• Proven track record of delivering innovation and continuous improvement.
For more information please call Michael on 01- or