Developer
cognizant
Job Description
- Design robust PySpark data pipelines that efficiently ingest transform and aggregate large scale media and entertainment datasets to support analytics and reporting needs
- Implement optimized PySpark code that enhances performance of batch and near real time data processing for audience metrics and content consumption patterns
- Collaborate with data engineers analysts and product teams in a hybrid work model to understand media business requirements and translate them into scalable technical solutions
- Develop reusable data frameworks and components that standardize processing of streaming video on demand and advertising data while ensuring consistency and reliability
- Apply data quality checks validation routines and monitoring mechanisms within PySpark workflows to maintain accurate and trustworthy data for content and revenue decisions
- Integrate data from multiple media platforms and content management systems into unified data models that enable holistic views of audience engagement and catalog performance
- Optimize storage formats partitioning strategies and execution configurations in PySpark to reduce processing time and infrastructure costs for large media datasets
- Collaborate with stakeholders to deliver clear and timely data outputs that support programming strategy recommendation engines campaign measurement and operational dashboards
- Document technical designs PySpark jobs data flows and configuration details to ensure maintainability and smooth handover across distributed development teams
- Ensure compliance with data governance security and privacy standards relevant to media and entertainment usage while working within day shift schedules
- Troubleshoot production pipeline issues perform root cause analysis and implement corrective actions to minimize disruption to critical reporting and analytics for content operations
- Contribute to continuous improvement initiatives by proposing enhancements to data pipeline architecture coding practices and automation capabilities in the PySpark ecosystem
- Support testing activities by preparing sample datasets validating outputs and collaborating with quality teams to ensure that delivered data solutions align with business expectations