Key Responsibilities

Data Operations & Quality

• Lead anddevelop a high-performing global data management organization, including dataanalysts and operations specialists, ensuring the capabilities, processes, andaccountability needed to deliver high-quality financial data and operationalexcellence.
  
• Driveoperational performance by managing KPIs and SLAs that support clientrequirements, data quality standards, delivery timelines, and overall serviceexcellence.
  
• Lead thealignment and standardization of operational reporting, KPI definitions, andperformance measures across the data organization, ensuring consistentperformance tracking and continuous process improvement.
  
• Establishscalable processes and tools that ensure accuracy, consistency, completeness,and timeliness across all datasets.
  
• Optimize datamanagement processes from end-to-end within the data value flow to increaseefficiency and reduce cost.
  
• Create aculture of continuous improvement, using KPIs, and automation to optimizeworkflows and elevate data quality.
  
• Drive adoptionof documentation, standardization, and best practices across the data analystfunction.
  
• Ensure fullcompliance with data governance, privacy, and security frameworks
  
• Build and runKPI driven data flow and quality measurement systems that optimizesproductivity serving as a basis for senior management reporting.
  
• Developcapacity and workforceplans aligned with business demand, ensuring the right organizationalstructure, skills, and resources are in place to support growth.
  
• Ensuresuccessful execution of contractual commitments by overseeing service deliveryperformance, monitoring compliance with agreed SLAs and obligations, andproactively addressing risks to client satisfaction and business outcomes.
  

Technology and AI

• Drive adoptionof emerging technologies, including LLMs and GenAI tools, to improve dataquality, automation, and decision-making capabilities.
  
• Partner with tech,product, and business leadership to prioritize data initiatives and ensuretimely, high-quality delivery.
  
• Establish andenforce data governance, quality, and security standards across all systems andteams.
  

Governance, Quality &Compliance

• Driveinitiatives to measure and improve data quality, consistency, andcompleteness.
  
• Implement andenforce data governance policies, data access controls, and lineage trackingwhile ensuring CEPRES’ strict data compliance and security regulations.
  

Stakeholder Enablement &Collaboration

• Serve as astrategic partner to product, engineering, commercial, and executiveteams.
  
• Provideinternal and external stakeholders with the tools, documentation, and trainingneeded to work effectively with data.
  

Requirements

Benefits

Originally posted on Himalayas