Databricks SME

Databricks Subject Matter Expert (Lead / Principal) Location: Dallas, TX (Hybrid) Employment Type: Contract-to-Hire About TURNBRIDGE TURNBRIDGE delivers precision-driven technical solutions and talent strategies that help organizations modernize, scale, and innovate. We focus on quality over volume—bringing deep technical expertise, transparency, and speed to every engagement. Role Overview TURNBRIDGE is seeking a Databricks Subject Matter Expert at the Lead / Principal level to serve as the firm’s top technical authority on the Databricks Lakehouse Platform. In this highly visible role, you will lead complex data transformation initiatives—from strategy and architecture through hands-on implementation and production deployment. You will partner closely with senior stakeholders to define data platform strategies, design scalable Databricks solutions, and mentor delivery teams. This role blends deep technical leadership with client advisory, pre-sales support, and practice development. Note: This role is based in Dallas, TX and follows a hybrid work model. Key Responsibilities Solution Architecture & Design • Lead end-to-end design of Databricks Lakehouse architectures, including Delta Lake, Unity Catalog, and medallion (bronze/silver/gold) data models • Define reference architectures, best practices, and reusable accelerators to support delivery consistency and scale • Evaluate and recommend deployment patterns across Azure Databricks, AWS Databricks, and GCP, aligning solutions with infrastructure, security, and governance requirements Data Engineering & Pipeline Development • Architect and oversee large-scale ETL/ELT pipelines using Apache Spark, Delta Live Tables, and Databricks Workflows • Design both real-time and batch ingestion frameworks for structured, semi-structured, and unstructured data • Establish standards for data quality, lineage, and observability leveraging Unity Catalog, Delta Lake features, and complementary tooling Machine Learning & MLOps • Guide teams on building end-to-end ML workflows using MLflow, Feature Store, and Databricks Model Serving • Advise on MLOps patterns including model versioning, monitoring, A/B testing, and automated retraining • Collaborate with data science teams to productionize models and integrate ML outputs into downstream applications Client Advisory & Engagement Leadership • Act as a trusted advisor to senior stakeholders on data platform strategy and Databricks adoption • Lead discovery sessions, architecture reviews, and technical assessments to define solution roadmaps • Support pre-sales efforts through solution design, effort estimation, proposal development, and technical demonstrations Thought Leadership & Practice Development • Contribute to internal intellectual property, including frameworks, accelerators, white papers, and training materials • Mentor and upskill consultants across the data practice, fostering a strong Databricks community of excellence • Represent TURNBRIDGE at industry events, partner summits, and webinars as a Databricks thought leader Required Qualifications • 10+ years of experience in data engineering, analytics, or platform architecture • 5+ years of hands-on experience with Databricks in enterprise production environments • Expert-level proficiency in Apache Spark (PySpark and/or Scala), Delta Lake, and SQL • Proven experience designing multi-cloud Lakehouse architectures (Azure, AWS, or GCP) • Strong hands-on experience with Unity Catalog for governance, access control, and lineage • Demonstrated success leading client-facing technical engagements and communicating with executive audiences • Background in consulting or professional services, managing multiple concurrent engagements • Bachelor’s degree in Computer Science, Engineering, Data Science, or equivalent practical experience Preferred Qualifications • Databricks certifications (Data Engineer Professional and/or Machine Learning Professional) • Experience with Delta Live Tables, Databricks Workflows, and Photon optimization • Familiarity with dbt, Infrastructure as Code (Terraform or Pulumi), and CI/CD pipelines for data platforms • Hands-on experience with MLflow, Feature Store, and Model Serving in production • Prior experience working within a Databricks partner ecosystem • Advanced degree (M.S. or Ph.D.) in a technical or quantitative discipline Core Skills • Apache Spark • Databricks Lakehouse Architecture • Data Quality & Governance • CI/CD for Data Platforms • Workflow Orchestration