Data Engineering Manager, Databricks
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Job Description
Data Engineering Manager building Databricks KPI models and pipelines for Blend’s AI services. Enabling governed scorecards, AI-generated narratives, and conversational analytics.
Responsibilities:
- Design, build, and maintain semantic layers and KPI models using Databricks Metric Views
- Define, validate, and translate KPI requirements into reusable data models and business logic with business owners
- Profile source data quality, ownership, data grain, and reconciliation requirements 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 analytics
- Collaborate with Business Analysts and AI Engineers to align KPI definitions with data structures and business ontologies
- Establish and enforce data quality, validation, and monitoring frameworks
- Implement security, access control, and governance practices
- Lead technical documentation and knowledge transfer at the conclusion of delivery phases
- Support production readiness assessments and oversee solution deployments to production environments
Requirements:
- 7+ years of experience in Data Engineering or related disciplines such as Data Architecture or Analytics Engineering
- Demonstrated expertise in semantic layer and KPI/metric modeling
- Strong hands-on experience building and maintaining Databricks Metric Views or equivalent semantic/metric layer tooling
- Advanced proficiency in SQL and Python
- Solid understanding of cloud data platforms, specifically Azure Databricks, and modern ELT/ETL tooling
- Demonstrated expertise in data modeling techniques, conformed dimensions, and Medallion-style architectures
- Experience profiling data quality, lineage, and reconciliation across multiple source systems
- Comfort working directly with business stakeholders to gather, validate, and implement KPI requirements
- Understanding of business ontology and semantic modeling concepts
- Proficiency with 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 a plus
- Advanced English required for effective communication with global teams
Benefits:
- Certifications in AWS, Databricks, and Snowflake
- Access to AI learning paths
- Study plans, courses, and additional certifications tailored to your role
- Access to Udemy Business
- 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 your location in LATAM
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