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Databricks Data Architect

Job in California City, Kern County, California, 93504, USA
Listing for: UNISON Group
Full Time position
Listed on 2026-08-29
Job specializations:
  • IT/Tech
    Data Engineering, Cloud Computing: Infrastructure & Operations, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 94406.4 - 141609.6 USD Yearly USD 94406.40 141609.60 YEAR
Job Description & How to Apply Below
  • 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 Work spaces, 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 Cloud Watch.
  • Collaborate with customers to build AI and LLM solutions leveraging MLflow, DBRX, and Mosaic AI.
Work Location:

Singapore 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, Dev Ops, 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 (Tensor Flow, PyTorch, Scikit-learn)
  • MLOps tools (MLflow, Kubeflow, Sage Maker, etc.)
  • Data platforms (Spark, Databricks, Snowflake)
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