jobs in Unison Group

Full Time Databricks Data Architect Jobs, in Unison Group Kuala Lumpur - Ricebowl

Databricks Data Architect

Unison Group

Undisclosed

KL City, Federal Territory

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Working Location

  • Kuala Lumpur Federal Territory Malaysia

Job Description

Responsibilities

  • 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.


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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