About this role
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