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:
Results-driven Azure Data Engineer with expertise in designing, building, and optimizing scalable data pipelines across cloud and distributed systems. Skilled in Python, PySpark, and SQL and AI-driven solutions for data ingestion, transformation, and integration, with a strong focus on improving efficiency, 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:
Big Data Technologies - HDFS, Hive, Apache Hadoop, Apache Spark
Data Streaming Frameworks - Confluent Kafka, Apache Kafka, KSQL
NoSQL Database - PostgreSQL, HBase
Programming Languages - PySpark, Unix
Cloud Platform - Azure Synapse, Azure, AWS, Cloudera
Job Scheduler - Airflow, AWS Glue, Control-M
Databases - Oracle 11g, MySQL, Netezza, IBM DB2, SSMS
Continuous Integration and Development (CI/CD) - Azure DevOps, GIT, Bitbucket
Container Technologies - AWS EKS, Docker
Cluster Management - Kubernetes, Pods
BI Tool - Power BI
IDE Tool - Eclipse, IntelliJ, PyCharm
ETL Tool - Informatica 10.2, IICS
Scripting Languages - Unix, Python
Domain Exposure - Insurance, Banking
Duties and Responsibilities:
- Lead end-to-end development and implementation of migration project.
- Design and implement scalable data pipelines that extract, load, and transform data from various product systems into the master data warehouse.
- Create metadata-driven frameworks to ensure data quality, consistency, and governance.
- Optimization of data-pipeline using parametrized ETL mapping in IICS ensuring high performance and scalability.
- Develop the PySpark code to create data pipeline, metadata sheet and transform logic.
- Build a scalable reconciliation framework in PySpark to support three-ways data reconciliation and ensure data integrity.
- Debug & resolve all kinds of job execution failures in Azure (Dam connector, cosmos, SCD, custom jobs, metadata, file level issues).
- Collaborate with discovery and analytics team to provide accessible and integrated data for migration.
- Peer reviewed the code and provided improvement comments and suggested spark optimization configuration to reduce the time of long running jobs.
- Worked closely with data analysts, and business stakeholders to deliver trusted, well-understood datasets aligned to business needs.
- Use Atlassian tools (Jira, Confluence, Bitbucket) for project management, documentation, and collaboration.
- Participate in design reviews, implementation walkthroughs, and production deployments.
- Collaborate with onsite and offshore teams to coordinate tasks, align processes,
- Integrate AI-powered solutions to enhance and automate development, testing, data pipeline, and documentation workflows.
Qualifications & Certifications (Optional):
- Degree in computer science, Engineering.
- “Algorithms & Data Structure” certification from IIT
Salary Range: >$100,000
Date of Posting: 19-Jun-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.
