Senior Technical Lead, Data Architecture & Design
Stryker · Gurugram
Work Flexibility: HybridSenior 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.