Cloud Data Engineer

What makes Cognizant a unique place to work? The combination of rapid growth and an 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

Results-driven Data Engineer with expertise in designing, building, and optimizing scalable data pipelines across cloud and distributed systems. Skilled in Python, PySpark, and SQL for data ingestion, transformation, and integration, with a strong focus on improving efficiency, reducing costs, and ensuring data quality. Experienced in metadata-driven frameworks, ETL process enhancements, and governance practices to deliver clean, reliable data for analytics and reporting. Adept at collaborating with cross-functional teams, monitoring platform performance, and driving continuous improvements to support business growth and decision-making.

Mandatory Skills

• Data Engineering: Azure Data Lake Storage (ADLS), Azure Blob Storage, Hadoop (HDFS, Hive), PySpark, SQL Server
• Cloud Platforms: Azure, AWS
• DevOps & Tools: Git, Bitbucket, CI/CD, Shell Scripting, JIRA, Agile Scrum
• Automation & Scheduling: Control-M, Sterling B2B Integrator
• Testing & APIs: Postman, API Testing, PyCharm, VS Code
• Monitoring and Logging: Skills in using monitoring tools and analysing the root cause using Spark Logs
• Security and Compliance: Understanding of security best practices and compliance requirements
• Business Domain Knowledge: Banking (BFSI)

Roles And Responsibilities

• Build and maintain scalable data pipelines using cloud services for ingestion, transformation, and storage.
• Develop data products that integrate customer data from multiple sources into unified profiles.
• Create metadata-driven frameworks to ensure data quality, consistency, and governance.
• Write Pyspark, and Spark SQL scripts to perform complex data transformations, ensuring data pipelines are efficient, scalable, and optimized for analytics and reporting.
• Support ETL processes by fixing errors, improving resiliency, and ensuring data integrity across reports and dashboards.
• Monitor data platforms, respond to alerts, and optimize pipelines for efficiency and cost reduction.
• Perform root cause analysis (RCA) for job failures and ensure stability after releases.
• Collaborate with onsite and offshore teams to coordinate tasks, align processes, and deliver projects smoothly.
• Participate in design reviews, implementation walkthroughs, and production deployments.
• Apply governance best practices to maintain security, lineage, and compliance with organizational and regulatory standards.
• Work closely with stakeholders and architects to capture requirements and deliver reliable solutions.
• Use Atlassian tools (Jira, Confluence, Bitbucket) for project management, documentation, and collaboration.
• Lead projects through effective planning, prioritization, and team coordination to ensure successful delivery.

Qualifications/Certifications

Databricks Certified Data Engineer Associate

Salary Range: 80k-90k

Date of Posting: 3/11/2026

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.