Senior Analyst- Data Quality & Automation (latam)

Johnson & Johnson Johnson & Johnson · Pharma · Mexico City, Mexico +1

This role focuses on ensuring supply chain data integrity and accuracy by implementing AI and automation solutions. It involves establishing data quality standards, identifying and resolving data discrepancies, and building automated workflows using tools like Python, SQL, and RPA to improve operational efficiency and decision-making. The role requires collaboration with cross-functional teams to gather requirements and implement solutions.

What you'd actually do

  1. Establish, monitor, and enforce data quality standards, rules, and governance across supply chain systems
  2. Proactively identify, investigate, and monitor data discrepancies, anomalies, and root causes affecting master data, transactional data, and reporting.
  3. Develop and maintain data quality dashboards, scorecards, and Key Performance Indicators to track health, completeness, and accuracy over time.
  4. Identify manual, repetitive, and error-prone processes and support implementation of automation solutions (e.g., RPA, Power Automate, Python, SQL scripts, ETL pipelines).
  5. Build, test, and deploy automated workflows that reduce cycle time and improve reliability of day-to-day supply chain operations.

Skills

Required

  • Bachelor's degree in Supply Chain, Data Analytics, Information Systems, Engineering, or a related field.
  • 7+ years of experience in supply chain data management, or analytics, with a focus on data quality and process automation.
  • Hands-on experience with data tools and automation platforms (SQL, Python, Power BI, Power Automate, RPA, ETL).
  • Strong knowledge of supply chain processes and master data domains (material, vendor, customer, BOM, inventory).
  • Proven ability to capture requirements and collaborate across diverse teams.

Nice to have

  • Experience in a regulated industry (pharmaceutical, medical devices, or consumer health).
  • Familiarity with SAP S/4HANA, data governance frameworks, and master data management (MDM) tools.
  • Experience with cloud data platforms (Azure, AWS, or Snowflake).
  • Lean Six Sigma or project management certification.

What the JD emphasized

  • driving AI and automation initiatives
  • scalable, automated data quality solutions
  • improve operational efficiency
  • data-driven decision-making
  • supply chain data management
  • process automation
  • data quality
  • automation solutions
  • automated workflows