Databricks Data Architect

Socket.dev; Charlotte (NC); On-site; USD 140,000 - 190,000; Full time

Job summary

Socket.dev is seeking a hands-on Databricks SME to design and optimize Delta Lakehouse architectures for enterprise AI solutions. You will own implementation tasks, lead technical delivery, and mentor teams in data governance and ML workflows.

You will implement scalable data pipelines, administer Databricks Workspaces, and automate deployments with Terraform and CI/CD. Expect collaboration with customers to deliver AI, LLM, and governance-enabled platforms.

Qualifications

• 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.

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.

Skills

Databricks

Delta Lake

DLT

Unity Catalog

SQL Warehouses

Python

Scala

Cloud ecosystems

Terraform

Git

CI/CD

MLflow

Monitoring

ML frameworks

Tools

Terraform

Git

CI/CD

MLflow

Kubeflow

SageMaker

Spark

Job description

• 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

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)