Description

Position Summary:

With over 7+ years of hands-on experience in Big Data, I specialize as a Big Data Developer, proficient in Py Spark, Spark SQL, HDFS, and HiveQL. I hold an DP-203 Data Engineer certification, further validating my expertise in data integration, processing, and management. I have successfully navigated comprehensive Software Development Life Cycles (SDLC) using both Waterfall and Agile methodologies. My expertise lies in large-scale data integration and processing through Apache Spark, alongside a proven ability to debug and optimize code in complex environments. I have led technical teams in delivering large-scale software development, operations, and integration projects, ensuring timely and successful execution. Adaptable to fast-paced and challenging environments, I excel in quick decision-making and managing high-pressure client interactions. Known for exceptional customer service, I bring strong analytical, troubleshooting, and problem-solving skills to the table. Collaborative team player with outstanding interpersonal skills, and I am committed to delivering results and continuously learning new technologies. My proactive attitude and dedication to tackling challenging tasks have been key to my professional growth and success.

Mandatory Skills:

1. Skills/Tools: Apache Spark, Py-spark, Spark SQL, HDFS, ADLS, Azure Synapse Analytics, ServiceNow, Control-M.

2. Database: Hive, MySQL.

3. Language and No-SQL: Python and HBase

4. Build Tools: Expertise in setting up and managing continuous integration and continuous deployment pipelines in Bitbucket and Jenkins

5. Job Scheduler: Familiarity with Control-M scheduling tool for ordering the Job pipeline.

6. Monitoring and Logging: Skills in using monitoring tools and analysing the root cause using Spark Logs

7. Security and Compliance: Understanding of security best practices and compliance requirements

8. Business Domain Knowledge: Banking

Duties and Responsibilities:

• Collaborate with cross-functional teams to analyse and understand complex functional requirements.

• Design, develop, and optimize data processing pipelines using Py Spark for diverse data transformations.

• Utilize Py Spark, Spark SQL, Spark Data Frames, Hive, ADLS and HDFS for scalable data ingestion and transformation.

• Implement performance tuning strategies to monitor and optimize Spark jobs for efficiency and resource utilization.

• Write Spark SQL and HiveQL queries tailored to project-specific requirements.

• Leverage Spark's Data Frames and Spark SQL for advanced data aggregation within transformation pipelines.

• Identify, research, and resolve root causes of production issues related to data ingestion and transformation.

• Enhance robustness and reliability in data workflows through proactive solutions.

• Configure and manage jobs using BMC Control-M, ensuring seamless scheduling and execution of data tasks.

• Manage version control with Git to track code changes and foster team collaboration.

• Create and implement Change Requests (CRQs) as part of project responsibilities.

• Ensure transparency by maintaining clear and comprehensive data documentation standards.

• Develop data ingestion and transformation code while adhering to best practices.

Individual Contribution:

• Received several GEM Awards for the succession of Prod Implementations

Salary Range: $85,000-$95,000

Date of Posting: 12/November/2025

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.