About this role
- 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.
Required Skills & Experience
- Strong 10+ hands-on experience with Databricks, including workspace setup, notebooks, clusters, and job orchestration.
- Expertise in Delta Lake, DLT, Unity Catalog, and SQL Warehouses.
- Strong 8+ Years of experience with Spark
- 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.
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