Azure Databricks Admin

Responsibilities

Architect and optimize big data pipelines using Apache Spark, Delta Lake, and Databricks-native tools.

Design scalable data ingestion and transformation workflows, including batch and streaming (e.g., Kafka, Spark Structured Streaming).

Create integration guidelines to configure and integrate Databricks with other existing security tools relevant to data access control.

Implement data security and governance using Unity Catalog, access controls, and data classification techniques.

Support migration of legacy systems to Databricks on cloud platforms like Azure, AWS, or GCP.

Manage cloud platform operations with a focus on FinOps support, optimizing resource utilization, cost visibility, and governance across multi‑cloud environments.

Act as a technical advisor to data engineering and analytics teams, guiding best practices and performance tuning.

Partner with architects and business stakeholders to align Databricks solutions with enterprise goals.

Lead proof‑of‑concept (PoC) initiatives to demonstrate Databricks capabilities for specific use cases.

Strategic & Leadership Contributions

Mentor junior engineers and promote knowledge sharing across teams.

Contribute to platform adoption strategies, including training, documentation, and internal evangelism.

Stay current with Databricks innovations and recommend enhancements to existing architectures.

Specialized Expertise (Optional but Valuable)

Machine Learning & AI integration using MLflow, AutoML, or custom models.

Cost optimization and workload sizing for large‑scale data processing.

Compliance and audit readiness for regulated industries.

Qualifications

Bachelor’s degree in computer science.

At least 6 years of experience in IT cloud infrastructure, architecture and operations, including security, with at least 3 years in a Platform admin role

Strong understanding of data security principles and best practices.

Expertise in Databricks platform, security features, Unity Catalog, and data access control mechanisms.

Experience with data classification and masking techniques.

Strong understanding of cloud cost management, with hands‑on experience in usage analytics, budgeting, and cost optimization strategies across multi‑cloud platforms.

Strong knowledge of cloud architecture, design, and deployment principles and practices, including microservices, serverless, containers, and DevOps.

Deep expertise in Azure/AWS big data & analytics technologies, including Databricks, real time data ingestion, data warehouses, serverless ETL, No SQL databases, DevOps, Kubernetes, virtual machines, web/function apps, monitoring and security tools.

Deep expertise in Azure/AWS networking and security fundamentals, including network endpoints & network security groups, firewalls, external/internal DNS, load balancers, virtual networks and subnets.

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