Data Engineering Manager, Databricks

This is a fully remote position, open to applicants in Chile.

📋 Description

• Create, develop, and maintain semantic layers and KPI models utilizing Databricks Metric Views

• Support governed executive scorecards and AI-driven analytical solutions

• Collaborate with business stakeholders to define, validate, and convert KPI requirements into reusable data models and business logic

• Assess source data quality, ownership, data granularity, and reconciliation needs across enterprise source systems

• Design and execute data integration and transformation pipelines for AI-generated narratives and conversational analytics

• Define standardized dimensions and market-specific data variations for multi-market reporting and analytics

• Work alongside Business Analysts and AI Engineers to align KPI definitions with data structures and business ontologies

• Establish and uphold data quality, validation, and monitoring frameworks across data assets

• Implement security, access control, and governance practices that align with platform and AI governance standards

• Lead the creation of technical documentation and knowledge transfer initiatives at the end of each delivery phase

• Assist with production readiness assessments and manage deployment to production environments

⛳️ Requirements

• Over 7 years of experience in Data Engineering or related fields like Data Architecture or Analytics Engineering

• Proven expertise in semantic layer and KPI/metric modeling

• Strong practical experience in building and maintaining Databricks Metric Views or similar semantic/metric layer tools

• Advanced skills in SQL and Python for data processing, transformation, and pipeline development

• Comprehensive understanding of cloud data platforms, particularly Azure Databricks, and modern ELT/ETL tools

• Demonstrated proficiency in data modeling techniques, conformed dimensions, and Medallion-style architectures

• Experience in assessing data quality, lineage, and reconciliation across various source systems

• Ability to work directly with business stakeholders to gather, validate, and implement KPI requirements

• Familiarity with business ontology and semantic modeling concepts

• Proficient in Git version control and collaborative development methodologies

• Understanding of how data engineering supports AI/LLM-based analytics, including feature preparation for narrative generation and conversational analytics

• Experience with FMCG/CPG or retail data ecosystems (POS, SKU, category, and market performance datasets) is advantageous

• Proficient in English: Advanced (necessary for effective communication with global teams)

🏝️ Benefits

• Certifications in AWS (we are AWS Partners), Databricks, and Snowflake

• Access to AI learning paths to keep up with the latest technologies

• Customized study plans, courses, and additional certifications relevant to your role

• Access to Udemy Business, providing thousands of courses to enhance your technical and soft skills

• English lessons to aid your professional communication

• Travel opportunities to attend industry conferences and meet clients

• Career development plans and mentorship programs

• Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones

• Company-provided equipment

• Flexible working arrangements

• Additional benefits may vary based on your location in LATAM