Databricks Data Architect
- Laiba Technologies LLC
3 Days Ago
NA
W2
San Francisco-CA
10-15 Years
Required Skills: Gold-Layer Data Models, Databricks, Delta Lake, Lakehouse Architecture, Medallion Architecture, Gold Layer
Job Description
We are seeking an experienced Databricks Data Architect to lead the design, development, and governance of enterprise data platforms. The ideal candidate will have strong hands-on Databricks expertise, experience building curated Gold-layer data models, and ownership of data quality, metric governance, data lineage, and AI data readiness.
Key Responsibilities
- Own data quality monitoring and alerting in Databricks, including alert coverage, issue triage, routing, SLAs, root-cause analysis, and resolution.
- Maintain data quality and anomaly detection checks as data pipelines evolve.
- Monitor and report data quality health to stakeholders.
- Define and govern enterprise metric definitions, calculations, and measurement standards across business functions.
- Establish metric certification standards and governance processes for official reporting.
- Mentor analysts, data engineers, and BI developers on data quality and metric governance practices.
- Collaborate with analytics engineers to architect and govern the Databricks Gold layer.
- Build certified data models with embedded data quality checks, anomaly detection, metric views, and data lineage.
- Lead data platform architecture, solution design, migration, and modernization initiatives.
- Drive AI data readiness through tiered dataset assessments covering completeness, accuracy, and automation readiness.
- Enable natural-language query experiences using certified and governed business metrics.
Required Skills
- 10–15 years of overall data engineering experience.
- Strong hands-on experience with Databricks.
- Experience developing curated and certified Gold-layer data models.
- Strong knowledge of Delta Lake and Lakehouse Architecture.
- Understanding of Medallion Architecture and Bronze, Silver, and Gold layers.
- Experience with data quality checks, data observability, and anomaly detection.
- Expertise in data quality alerting, SLA management, issue triage, and root-cause analysis.
- Experience with metric definitions, metric certification, and governance.
- Knowledge of semantic layers, metric views, data lineage, and data catalogs.
- Experience architecting or leading data platform builds, migrations, or modernization initiatives.
- Ability to lead technical discussions and mentor cross-functional teams.
Preferred Skills
- Supply chain data engineering and analytics experience.
- AI data readiness and dataset assessment experience.
- Natural-language querying and governed analytics experiences.
- Experience collaborating with analytics engineering and BI teams.
Expected Deliverables
- Governed Databricks Gold-layer data models with embedded data quality and anomaly checks.
- Reliable data quality alerting, monitoring, SLA tracking, and issue resolution processes.
- Certified business metrics with standardized definitions and governance controls.
- Documented metric views, semantic models, and data lineage.
- Data readiness assessments covering completeness, accuracy, and automation readiness.
- Scalable data platform architecture supporting analytics and AI-driven use cases.
