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Databricks Data Architect

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Unison Group · Charlotte, NC · Full-time

Build · Found · posted 20 days ago

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This posting never puts a number on it, or names several that contradict each other. Read the requirements below before you rule yourself out — we would rather say nothing than guess at it.

• We're seeking a hands-on experience in Databricks with deep technical expertise in building and optimizing Lakehouse-based data and AI solutions. • In this role, you'll design, develop, and operationalize Delta Lakehouse architectures using Databricks, driving real-world outcomes for enterprise customers. You'll take ownership of implementation tasks, lead technical delivery, and mentor engineering teams in best practices across data engineering, governance, and AI Key Responsibilities • Design and implement scalable data pipelines using Delta Live Tables (DLT), Spark SQL, Python, or Scala • Optimize ETL, streaming, and ML workloads for performance, cost efficiency, and reliability • Administer and configure Databricks Workspaces, Unity Catalog, and cluster policies for secure, governed environments • Automate infrastructure and deployments using Terraform, Git, and CI/CD pipelines • Implement observability, cost optimization, and monitoring frameworks using tools like Splunk, Prometheus, or CloudWatch • Collaborate with customers to build AI and LLM solutions leveraging MLflow, DBRX, and Mosaic AI Work Location: Singapore Requirements Required Skills & Experience • Strong hands-on experience with Databricks, including workspace setup, notebooks, clusters, and job orchestration • Expertise in Delta Lake, DLT, Unity Catalog, and SQL Warehouses • Proficiency in Python or Scala for data engineering and ML workflows • Strong understanding of AWS, Azure, or GCP cloud ecosystems • Experience with Terraform automation, DevOps, and MLOps practices • Familiarity with monitoring and governance frameworks for large-scale data platforms Good to Have Skills: • Machine Learning, Deep Learning, NLP, or Generative AI • Designing distributed and scalable systems • API-first and microservices architecture • Python, ML frameworks (TensorFlow, PyTorch, Scikit-learn) • MLOps tools (MLflow, Kubeflow, SageMaker, etc.) • Data platforms (Spark, Databricks, Snowflake)

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