Enterprise Architect - Databricks

12+ years of experience in data architecture, data engineering, or enterprise analytics — with at least 5 years focused on Databricks platform delivery.

Databricks Certified Data Engineer Professional or Databricks Certified Associate Developer for Apache Spark — required. Additional Databricks certifications strongly preferred.

Expert-level proficiency in Apache Spark (PySpark, Scala Spark) — performance tuning, DAG optimization, shuffle management, and broadcast strategies.

Deep hands-on expertise with Delta Lake: ACID transactions, Z-ordering, OPTIMIZE, VACUUM, time travel, and schema enforcement/evolution.

Proven production experience with Delta Live Tables (DLT): expectations, quarantine patterns, SCD Type 1/2 in DLT, and pipeline monitoring.

Strong Unity Catalog implementation experience: catalog/schema/table hierarchy design, privilege inheritance, service principals, and attribute-based access control.

Experience architecting Databricks on at least one major cloud: Azure Databricks (ADLS Gen2, Azure AD), AWS (S3, IAM Instance Profiles, Glue Catalog), or GCP (GCS, Dataproc comparison).

Proficiency in infrastructure-as-code for Databricks: Terraform (databricks provider), Databricks Asset Bundles (DABs), and CI/CD integration (GitHub Actions, Azure DevOps, Jenkins).

Hands-on MLflow experience: experiment tracking, model registry, model serving, and custom pyfunc models.

Strong SQL expertise for Databricks SQL / Photon query optimization, materialized views, and lakehouse serving patterns.

Experience with real-time streaming architectures: Kafka + Databricks Structured Streaming, Autoloader, and watermarking strategies.

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