Data Engineering Manager, Databricks

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

📋 Description

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

• Identify, verify, and convert KPI requirements into reusable data models and business logic in collaboration with business stakeholders.

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

• Design and implement data integration and transformation pipelines for AI-driven narratives and conversational analytics.

• Establish conforming dimensions and market-specific data variations for reporting and analytics across multiple markets.

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

• Create and uphold frameworks for data quality, validation, and monitoring.

• Apply security measures, access controls, and governance practices.

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

• Assist in production readiness assessments and manage solution deployments to production environments.

⛳️ Requirements

• Over 7 years of experience in Data Engineering or related fields, including Data Architecture or Analytics Engineering.

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

• Extensive hands-on experience in building and maintaining Databricks Metric Views or similar semantic/metric layer tools.

• Advanced skills in SQL and Python.

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

• Proven experience in data modeling techniques, conformed dimensions, and Medallion-style architecture.

• Experience in profiling 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 concepts of semantic modeling.

• Proficiency in Git version control and collaborative development methodologies.

• Understanding 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 advantageous.

• Advanced English proficiency required for effective communication with international teams.

🏝️ Benefits

• Certifications in AWS, Databricks, and Snowflake.

• Access to AI learning paths.

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

• Access to Udemy Business.

• English language lessons.

• Opportunities for travel to industry conferences and client meetings.

• Career development plans and mentorship initiatives.

• Special rewards for birthdays, work anniversaries, and personal milestones.

• Company-provided equipment.

• Flexible working arrangements.

• Additional benefits may vary based on your location in LATAM.