Data Engineering Manager, Databricks

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

📋 Description

• Create, develop, and sustain semantic layers and KPI models leveraging Databricks Metric Views.

• Construct governed executive scorecards and AI-driven analytical solutions.

• Collaborate with business stakeholders to identify, confirm, 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 implement data integration and transformation pipelines for AI-generated narratives and conversational analytics.

• Define conformed dimensions and market-specific data variations for multi-market reporting and analysis.

• Work alongside Business Analysts and AI Engineers to ensure alignment of KPI definitions with data structures and business ontologies.

• Establish and uphold data quality, validation, and monitoring frameworks.

• Implement security measures, access controls, and governance practices in line with platform and AI governance standards.

• Lead technical documentation and knowledge transfer at the end of delivery phases.

• Assist in production readiness evaluations and supervise solution deployments to production environments.

⛳️ Requirements

• Over 7 years of experience in Data Engineering or related fields such as Data Architecture or Analytics Engineering.

• Proven expertise in semantic layer and KPI/metric modeling.

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

• Advanced skills in SQL and Python.

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

• Proficient in data modeling techniques, conformed dimensions, and Medallion-style architectures.

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

• Background in directly working with business stakeholders to collect, validate, and execute KPI requirements.

• Familiarity with business ontology and concepts of semantic modeling.

• Proficient in Git version control and collaborative development practices.

• Knowledge of data engineering for AI/LLM-based analytics, including feature preparation for narrative generation and conversational analytics.

• Experience with FMCG/CPG or retail data ecosystems is an advantage.

• Advanced English proficiency is required for effective communication with global teams.

🏝️ Benefits

• Daily lunches at headquarters, featuring vegetarian, vegan, gluten-free, and sugar-free options.

• Gourmet meals provided every Friday by an on-site chef.

• Flexible working arrangements.

• Provision of a MacBook and accessories.

• Availability of snacks and beverages daily at headquarters.

• After-work events, including football, tennis, and game nights at headquarters.

• Football league matches every Wednesday and Friday.

• Access to tennis courts for casual games.

• Chess tournaments, game nights, and music events.

• Opportunities for AWS certifications, study plans, courses, and other certifications.

• English language lessons available.

• Learning opportunities during Tech Tuesdays.

• Mentoring and professional development opportunities.

• Gifts for anniversaries and birthdays.