TELECOMMUTE Databricks Architect

Class Valuation, LLC

United States

8 days ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

Artificial Intelligence Amazon Web Services Microsoft Azure Code Review Continuous Integration Data Architecture Data Security Distributed Systems Python (Programming Language) Standard Sql Scala (Programming Language) Search Technologies

+10 more

SQL Databases Data Streaming Google Cloud Cloud Platform System Apache Spark Data Lakes Information Technology Machine Learning Operations Software Coding Databricks

Job description

Lead customer-facing Databricks engagements from discovery and architecture through production deployment and adoption.
Design and develop Databricks Apps and production-grade data/AI solutions using Python or Scala, SQL, Apache Spark, Delta Lake, and Databricks platform services.
Build reference architectures and scalable solutions across batch/streaming data engineering, analytics, AI/ML, and GenAI use cases.
Own technical delivery: write and review code, troubleshoot complex issues, tune Spark workloads, and improve performance, reliability, and cost.
Implement CI/CD, MLOps, security, governance, observability, and operational best practices for enterprise deployments.
Partner with customer stakeholders, project managers, account teams, engineering, and support to manage scope, risks, dependencies, and escalations.
Translate complex technical concepts into clear recommendations, phased roadmaps, and measurable customer outcomes.

Requirements

17+ years of overall IT experience, including senior architecture, engineering, consulting, or platform delivery responsibilities.
5+ years of recent, hands-on experience across the Databricks ecosystem; demonstrated delivery of multiple production implementations.
Strong Databricks Apps development experience, including secure application architecture, data access, deployment, and lifecycle management.
Deep expertise in Apache Spark and distributed computing, including runtime behavior, optimization, scalability, and production troubleshooting.
Advanced coding skills in Python and/or Scala plus strong SQL and data architecture fundamentals.
Deep expertise in at least one cloud platform (AWS, Azure, or Google Cloud Platform) and working knowledge of a second.
Proven consulting and executive-facing communication skills, with the ability to build trust and guide technical decisions. HIGHLY PREFERRED
Hands-on AI/ML or GenAI experience on Databricks, including MLflow/Mosaic AI, model serving, vector search, RAG, agents, or production MLOps.
Databricks Data Engineer Professional or comparable Databricks certification.
Experience scoping professional services engagements, estimating effort, and defining technical deliverables.