What makes Cognizant a unique place to work? The combination of rapid growth and a unique place international and innovative environment! This is creating many opportunities for people like YOU — people with an entrepreneurial spirit who want to make a difference in this world.
At Cognizant, together with your colleagues from all around the world, you will collaborate on creating solutions for the world's leading companies and help them become more flexible, more innovative, and successful. Moreover, this is your chance to be part of the success story.
Position Summary:
We are seeking an experienced Data Architect with strong expertise in Azure Data Engineering, Databricks, PySpark, ETL/ELT development, data warehousing, and cloud-based analytics platforms. The role requires hands-on experience in designing, building, optimizing, and supporting scalable data solutions across batch, streaming, API-based, and file-based ingestion patterns. The candidate will be responsible for delivering reliable, secure, and high-performing data pipelines while collaborating with business stakeholders, architects, and cross-functional delivery teams in Agile and Waterfall environments.
Mandatory Skills:
- Proven hands-on experience in designing, developing, and delivering enterprise-scale data engineering and analytics solutions using Databricks SQL, Databricks Workflows, and PySpark across complex business environments.
- Strong expertise in building scalable data pipelines, data transformation frameworks, and high-performance analytics solutions leveraging modern cloud-based data platforms.
- Extensive experience with Azure Databricks, including Unity Catalog, Delta Live Pipelines (DLT), and Azure Data Lake Storage (ADLS) for secure, governed, and reliable data management.
- Demonstrated capability in architecting and implementing end-to-end data Lakehouse solutions, ensuring data quality, governance, lineage, and operational excellence.
- Proficiency in Python and Spark (Scala/PySpark) for developing robust, optimized, and reusable data processing frameworks and analytical workloads.
- Experience with Azure DevOps, CI/CD pipelines, release management, version control, and Agile delivery methodologies to support continuous integration and deployment practices.
- Strong understanding of data architecture principles, design patterns, performance optimization techniques, and cloud-native solution structuring for large-scale data ecosystems.
- Experience in requirements analysis, effort estimation, resource planning, proposal preparation, solution design, and delivery governance for data modernization and transformation initiatives.
- Strong exposure to Agile ways of working, including sprint planning, backlog grooming, PI planning, retrospectives, and cross-functional collaboration within Agile Release Trains.
- Excellent communication, presentation, and consulting skills with the ability to influence strategic decisions, build trusted client relationships, and drive customer-centric outcomes.
Duties and Responsibilities:
- Collaborate with business stakeholders, solution architects, and development teams to gather, analyze, and translate complex business requirements into scalable data platform solutions.
- Lead end-to-end delivery of enterprise data warehouse, data lake, and analytics initiatives using Azure Data Factory, Azure Databricks, Azure Synapse, and Azure Data Lake Storage Gen2.
- Design and implement robust ETL/ELT frameworks for batch, streaming, API-based, and file-based data ingestion using Python, PySpark, Event Hub, and Databricks.
- Perform source system analysis, data profiling, and data mapping activities to ensure accurate and efficient migration and integration of business-critical data.
- Develop and optimize data pipelines, transformation logic, and processing frameworks to improve performance, scalability, and operational efficiency across the data platform.
- Establish and enforce data quality, validation, and governance standards by implementing automated checks and reconciliation processes across data pipelines.
- Lead technical teams across multiple projects, providing guidance on architecture, design patterns, coding standards, performance tuning, and best practices.
- Manage project delivery lifecycle including requirement gathering, solution design, estimation, sprint planning, development, testing, deployment, and production support activities.
- Drive Agile delivery practices through sprint planning, backlog refinement, status tracking, risk management, and stakeholder reporting using Azure DevOps and Jira.
- Work closely with business users, data owners, and cross-functional teams to resolve data-related issues and ensure successful implementation of business requirements.
- Design and implement dimensional data models, including Fact and Dimension tables, leveraging industry-standard approaches such as SCD Type 1 and Type 2 methodologies.
- Facilitate customer engagement, technical workshops, solution walkthroughs, and architecture reviews to align business objectives with technical deliverables.
Qualifications & Certifications (Optional):
15+ years of IT experience in data engineering, data warehousing, ETL/ELT development, cloud data platforms, and technical delivery leadership.
Microsoft Certified: DP-203 Data Engineering on Microsoft Azure.
Microsoft Certified: DP-900 Microsoft Azure Data Fundamentals.
Microsoft Certified: PL-900 Power Platform Fundamentals.
Microsoft Certified: DP-600 Microsoft Fabric Analytics Engineer.
Databricks Data Engineer Associate Certification.
Salary Range: >$100,000
Date of Posting: 27-Jul-26
Next Steps: If you feel this opportunity suits you, or Cognizant is the type of organization you would like to join, we want to have a conversation with you! Please apply directly with us.
For a complete list of open opportunities with Cognizant, visit http://www.cognizant.com/careers. Cognizant is committed to providing Equal Employment Opportunities. Successful candidates will be required to undergo a background check.
