POSITION Databricks Architect
LOCATION remote
DURATION 6+month
REQUIRED SKILLS
7+ years of experience in data architecture, data engineering, or platform engineering roles, with at least 3+ years focused on Databricks platform architecture.
Expert-level knowledge of Databricks platform components: Unity Catalog, Delta Lake, Delta Live Tables, Workflows, SQL Warehouses, MLflow, and Databricks SQL.
Deep expertise in Unity Catalog governance, including metastore design, catalog/schema strategies, permission models, data lineage, and multi-workspace/multi-cloud patterns.
Strong architectural background in cloud platforms (Azure, AWS, or Google Cloud Platform), including storage services, identity management (Azure AD, AWS IAM), networking, and security best practices.
Proven experience designing enterprise-scale data architectures, including medallion/multi-hop architectures, data mesh patterns, domain-driven design, and data product frameworks.
Hands-on experience with infrastructure-as-code (Terraform, ARM templates, CloudFormation) for platform configuration and governance automation.
Strong understanding of DevOps practices, CI/CD pipelines, version control strategies, and automated testing for data platforms.
Experience with performance tuning, cost optimization, and capacity planning for large-scale data platforms.
Preferred Qualifications
Databricks certification (e.g., Databricks Certified Data Engineer Professional, Solutions Architect). Note: Certification alone is insufficient; candidates must demonstrate current hands-on technical execution aligned with certification level.
Cloud certifications such as Azure Solutions Architect, AWS Solutions Architect, or Google Cloud Platform Professional Data Engineer.
Experience designing multi-tenant architectures with secure data isolation, cross-tenant data sharing, and compliance controls.
Background in streaming architectures using Structured Streaming, Kafka, Event Hubs, or Kinesis.
Exposure to machine learning operations (MLOps), feature stores, model serving, and AI/ML platform architecture.
Experience with data mesh implementations, federated governance, and distributed data ownership models.
Knowledge of analytics platforms (Power BI, Tableau, Looker) and their integration patterns with Databricks.
Familiarity with domain-specific data models in education (CEDS), healthcare, finance, or operational domains.
Experience with real-time CDC patterns, change data capture tools (Debezium, Qlik, Fivetran), and event-driven architectures.
Leadership & Soft Skills
Professional presence and composure under pressure, including ability to handle unexpected technical challenges, maintain calm in production incidents, and communicate effectively during high-stress situations.
Strategic thinking with ability to balance long-term architectural vision with pragmatic, incremental delivery.
Exceptional communication skills to articulate complex architectural concepts to technical and non-technical stakeholders, including executive leadership.
Proven ability to influence and drive consensus across multiple teams and organizational levels.
Mentorship and enablement mindset to uplift engineering teams through knowledge sharing, documentation, and hands-on guidance.
Strong problem-solving capabilities with a focus on root cause analysis and sustainable solutions.
Commitment to quality, including comprehensive documentation, architectural decision records (ADRs), and knowledge transfer.
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