Data Engineering Manager, Databricks

Posted 1ds ago

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Data Engineering Manager building Databricks KPI models and pipelines. Supporting Blend’s AI-powered analytics and governed executive scorecards.

Design, build, and maintain semantic layers and KPI models using Databricks Metric Views
Underpin governed executive scorecards and AI-powered analytical solutions
Work directly with business owners to define, validate, and translate KPI requirements into reusable data models and business logic
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 across data assets
Implement security, access control, and governance practices aligned with platform and AI governance standards
Lead technical documentation and knowledge transfer initiatives at the conclusion of each delivery phase
Support production readiness assessments and oversee solution deployments to production environments

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 for data processing, transformation, and pipeline development
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 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 is a plus
English: Advanced (required for effective communication with global teams)

At-home medical assistance via EMI (or similar provider) through Asobursatil, available for all employees from AllStar to Analyst level
Private healthcare plans for Lead-level roles and above
Christmas kit delivered to all employees
1 day off for academic graduation
Family Day: 1 day off every semester (must be taken within the same semester)
Savings incentive program via Asobursatil: Year 1: Blend contributes 50% of your monthly savings; Year 2: Blend contributes 100% of your monthly savings; Year 3+: Blend contributes 150% of your monthly savings
Savings can be withdrawn in July and December
Forgivable education loans subject to committee approval and budget availability
Retention-based forgiveness schedule applies after program completion