We are looking for an experienced Supply Chain Data Engineer with strong hands-on expertise in Databricks, Data Quality, Metric Governance, and Data Platform Modernization.
Key Responsibilities
Own data quality monitoring, alerting, issue triage, SLA management, root-cause analysis, and resolution within Databricks.
Establish and govern enterprise-wide metric definitions, calculations, measurement standards, and certification processes.
Architect and manage the Databricks Gold Layer, including certified data models, metric views, embedded data quality checks, and data lineage.
Drive AI readiness through dataset quality assessments, automation readiness, and natural-language query experiences.
Collaborate with analytics engineers, data engineers, and BI teams to establish scalable data governance standards.
Mentor and guide analysts, data engineers, and BI developers.
Required Skills
Strong hands-on experience with Databricks, Delta Lake, Lakehouse Architecture, Medallion Architecture, and Gold Layer data models.
Expertise in Data Quality, Data Observability, Anomaly Detection, Alerting, and SLA Management.
Experience with Metric Governance, Semantic Layers, Metric Views, Data Lineage, and Data Catalogs.
Proven experience in Solution Architecture, Data Platform Transformation, Migration, or Modernization.
Preferred Qualifications
Supply Chain or Hardware Operations domain experience.
AI Readiness, AI/BI, Text-to-SQL, or Natural Language Query experience.
Experience mentoring or leading engineering teams.
Senior-level experience with strong ownership and architectural capabilities.
Candidates with an Open to Work profile are encouraged to apply.
Interested in this opportunity or know someone who would be a great fit?
Please reach out directly.
Email:
