Lead Data Engineer

• Build and maintain scalable data pipelines and data solutions in Databricks using Unity Catalog and Delta
• Curate Genie spaces and semantic layers with metadata, certified metric definitions, example SQL, and trusted assets
• Maintain and refactor Git/GitHub repositories and develop modular, reusable data components
• Implement CI/CD workflows and promote Databricks solutions from development to controlled UAT environments
• Model marketing performance data, including email events, campaign and promotion history, offers, packages, and tours
• Build point-in-time audience histories and connect marketing sends with downstream sales outcomes
• Develop person- and household-grain data solutions using ID crosswalks and identity-match rules
• Implement suppression, consent, Do Not Email, marketability, and PII-handling requirements
• Ingest and integrate SQL Server enterprise data warehouse data
• Translate legacy SQL audience logic into governed definitions
• Deliver audiences from Databricks to Adobe Campaign or Segment with service accounts, encryption, and auditing
• Profile unfamiliar data sources and produce data dictionaries and ERDs
• Develop data-quality tests and validated query/result sets
• Collaborate with analytics, engineering, marketing, data, and security teams

• 5+ years of experience in Data Engineering or similar roles
• Hands-on experience developing data pipelines in Databricks, including Unity Catalog and Delta
• Strong hands-on experience with Python for data processing and transformation
• Strong SQL skills, including understanding and translating complex existing SQL logic
• Experience with Git-based development and CI/CD, preferably using Databricks Asset Bundles or equivalent
• Experience with Azure and promoting data solutions across development and controlled UAT environments
• Experience modeling data for marketing analytics, customer data, or similar business domains
• Experience with customer identity, person/household data, ID crosswalks, and identity matching rules
• Experience handling consent, suppression, marketability, and PII requirements
• Experience integrating data from SQL Server enterprise data warehouses
• Ability to independently profile unfamiliar data sources and document findings through data dictionaries and ERDs
• Strong analytical and problem-solving skills
• Strong communication and collaboration skills
• Excellent written and verbal English

• Certifications in AWS, Databricks, and Snowflake
• Access to AI learning paths
• Study plans, courses, and additional certifications tailored to the role
• Access to Udemy Business courses
• English lessons
• Travel opportunities to attend industry conferences and meet clients
• Career development plans and mentorship programs
• Special day rewards for birthdays, work anniversaries, and other personal milestones
• Company-provided equipment
• Flexible working options
• Other benefits may vary according to location in LATAM