Data Engineer

• Data Pipeline Operations:
  • Manage and maintain Linux-based data pipelines, ensuring data flows efficiently and accurately
  • Develop and maintain shell scripts to automate data processing, transformation, and loading
  • Collaborate with data engineers to optimize data workflows and improve data quality
  
• Job Scheduling and Release Management:
• Create, schedule, and manage jobs in Control-M to ensure timely data processing and delivery
• Work with the planning team to plan and execute releases, ensuring minimal disruption to data operations
• Monitor job execution, analyze logs, and troubleshoot job failures to ensure data integrity
  
  Incident Management:
  • Identify and respond to data-related incidents, minimizing impact on operations and stakeholders
  • Conduct root cause analysis to prevent recurrence and improve data quality
  • Document incident details, resolution steps, and lessons learned for future reference
  
  Data Management:
• Manage databases, run queries, and troubleshoot connectivity issues to ensure data availability
• Collaborate with data analysts and engineers to improve data governance and quality
• Develop and maintain data quality checks to ensure data accuracy and integrity
  
  Soft Skills:
  • Analytical thinking to troubleshoot and resolve data-related issues
  • Effective communication with stakeholders to ensure data needs are met
  • Flexibility and adaptability to handle changing data requirements and priorities

Nice to Have:

• Basic knowledge of Ab Initio development and data governance principles
• Experience with version control systems like Git
• Familiarity with mainframe systems for data transfer and integration