Solution Architect, Delivery, Databricks
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Job Description
Remote Solution Architect designing Databricks Lakehouse platforms, migrations, governance, and cloud data architectures. Advising enterprise clients for Infinitive, a data and AI consultancy.
Responsibilities:
- Design enterprise-scale, production-ready Lakehouse solutions using the Databricks Data Intelligence Platform, Medallion Architecture, Delta Lake, and Databricks SQL
- Architect and configure enterprise security and governance models using Unity Catalog, row/column-level filtering, data masking, ABAC, and Delta Sharing
- Lead strategy and technical execution for migrating legacy data warehouses and Hadoop platforms to Databricks
- Define batch and low-latency streaming patterns using Structured Streaming, Delta Live Tables, Auto Loader, and Apache Spark
- Lead engineering pods by establishing reference architectures, conducting architectural reviews, reviewing pull requests, and standardizing CI/CD pipelines
- Diagnose and resolve Spark and Delta performance bottlenecks, optimizing query plans, partitioning, Z-Ordering, caching, and Photon configurations
- Establish compute governance, cluster policies, auto-termination/autoscaling rules, serverless compute configurations, and chargeback/showback tagging models
- Partner with ML and AI engineers to integrate MLflow, Feature Store, Model Serving, and Vector Search/RAG pipelines
- Advise client Chief Architects, Directors of Engineering, and CDOs through technical workshops, design sessions, and POC evaluations
- Collaborate with Databricks Partner Solutions Architects and field engineering on platform capabilities and best-practice alignment
- Create reusable architectural blueprints, reference architectures, migration accelerators, and boilerplate configurations for Infinitive’s IP library
Requirements:
- 8+ years in data architecture, data engineering, or enterprise software development
- At least 3+ years architecting enterprise solutions centered on Apache Spark and the Databricks Data Intelligence Platform
- Databricks Certified Data Engineer Professional or Databricks Certified Machine Learning Professional certification
- Deep architectural proficiency in at least one major cloud platform: AWS, Azure, or GCP
- Knowledge of VPC/VNet networking, private endpoints, cloud IAM/Entra ID integration, and cloud object storage such as S3, ADLS Gen2, or GCS
- Mastery of dimensional modeling, Data Vault, and Medallion design
- Production experience implementing Unity Catalog across multi-workspace environments
- Advanced programming skills in Python, PySpark, and SQL
- Production experience with Terraform and orchestrators such as Databricks Workflows or Airflow
- Proven experience leading technical delivery teams, translating functional requirements into architectural blueprints and user stories, and resolving critical delivery blockers
- Preferred: experience integrating Databricks with Power BI, Tableau, reverse ETL, dbt, or data observability platforms
- Preferred: experience with HIPAA, HITRUST, SOC2, or FedRAMP-compliant architectures
- Active Public Trust or Secret clearance, or eligibility to obtain, is a plus
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