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. Required Skills & Experience - 6 to10 Years for 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 governanceframeworks for large-scale data platforms.
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