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/Py. Spark, 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