Senior Technical Lead, Data Architecture & Design

Work Flexibility: Hybrid

Senior Technical Lead:

We are looking for an experienced Senior Technical Lead to lead the end-to-end delivery of scalable, secure, and high-performing enterprise data built on Azure and Databricks.

The role will work closely with Enterprise Architecture, Platform & Engineering, Business Analysts, Implementation Partners, Product Owners, 
and Service Delivery Teams to ensure successful delivery from solution design through production deployment and transition to service delivery.

What you will do:

• Engage with delivery partners in technical discussions, solution reviews, and design evaluations.
• Provide technical guidance and oversight throughout the delivery lifecycle to delivery partners.
• Ensure solutions adhere to approved architecture, engineering standards, governance requirements, and best practices.
• Lead the implementation of ETL/ELT pipelines, data lakes/lakehouses, data warehouses, BI integrations, and reusable data products.
• Drive alignment on standards across security, privacy and compliance requirements with implementation partners.
• Optimize performance, scalability, reliability, and cloud cost efficiency across data platforms and solutions.
• Own end-to-end technical delivery including solution design, development, testing, deployment, hypercare, and transition to operations.
• Guide teams in following approved CI/CD and version control standards, with a strong emphasis on automated, consistent, and reliable deployments through Azure DevOps.
• Review data solutions, technical assessments, change-impact analysis, and risk identification and mitigation.
• Collaborate with Enterprise Architecture, Platform, PMO, Business Analysts, Product teams and other internal cross-functional stakeholders.
• Mentor data engineers and analysts and promote engineering standards, design best practices, and continuous improvement.

What you need:

• Bachelor's degree in Computer Science, Data Analytics, or a related field. Degree in Statistics, and Data Science is an added advantage.
• 10-12 years of related data engineering and architecture experience.
• Strong experience in enterprise data engineering and data architecture.
• Hands-on expertise with Azure Databricks, Azure Data Factory/Synapse, ADLS, SQL, Spark/PySpark, and Delta Lake.
• Strong understanding of data modeling, ETL/ELT architecture, data governance, security, and access-control concepts.
• Experience designing scalable cloud data platforms and optimizing performance and cost.
• Experience with CI/CD and Azure DevOps for automated code promotion and deployment.
• Strong understanding of testing, release management, production deployment, and operational support practices.

Travel Percentage: None