Technical Lead (Azure Data Factory)

Key Responsibilities

Technical Leadership

• Lead and validate the design, architecture, and deployment of the Microsoft Fabric Data Platform in collaboration with implementation partners.
• Provide technical guidance and mentorship to developers, data engineers, and analysts.
• Define and enforce standards for coding, data modelling, and overall solution design.

Design and Implementation

• Design and implement scalable, secure, and high-performing data solutions using Microsoft Fabric.
• Architect and contribute to the development of data pipelines for ingestion, transformation, and processing of large datasets.
• Ensure adherence to governance, compliance, and security standards across the platform.

Collaboration and Stakeholder Engagement

• Collaborate with business stakeholders to capture user stories and translate them into technical requirements and delivery plans.
• Work closely with DevOps teams to define and enhance CI/CD pipelines and automated deployment processes.
• Coordinate with DTS and business-led technology teams to ensure secure access to systems and applications.
• Partner with data analysts to maximize platform adoption and analytical efficiency.

Quality Assurance and Performance

• Conduct code reviews and enforce quality assurance best practices.
• Monitor platform performance, data pipelines, and processing workflows, resolving issues proactively.
• Define and implement testing strategies, including regression testing, with a strong focus on automation.

Documentation and Knowledge Sharing

• Develop and maintain comprehensive documentation covering architecture, processes, and workflows.
• Deliver or facilitate training and knowledge-sharing sessions for technical teams and stakeholders.

Required Technical Skills and Experience

• Proven hands-on experience implementing Microsoft Fabric.
• Strong expertise in Azure data services including Azure Data Factory, Azure Synapse Analytics, Azure Databricks, Azure Blob Storage, and Azure SQL Database.
• Solid experience with data modelling, ETL/ELT processes, and data pipeline orchestration.
• Proficiency in Python, Spark, Scala, and SQL.
• Experience with infrastructure as code tools such as Terraform, Azure Resource Manager templates, GitLab, or GitHub.
• Hands-on experience with Azure DevOps and CI/CD pipelines.
• Strong understanding of security, governance, and compliance in enterprise data platforms.