Platform Engineer

Are you passionate about building and optimizing modern cloud data platforms? We’re seeking a Senior Data Platform Engineer to help drive the evolution of a large-scale enterprise data ecosystem across Azure, Databricks, governance, security, and analytics platforms.

In this highly visible role, you’ll be responsible for designing, engineering, and supporting scalable data platforms that enable analytics, AI/ML, and Business Intelligence initiatives while ensuring performance, security, governance, and cost efficiency.

What You’ll Be Doing

• Design, build, and support cloud-native data platforms using Microsoft Azure, Databricks, Delta Lake, and Azure Data Lake Storage
• Develop and optimize enterprise data pipelines, ETL/ELT processes, and lakehouse architectures
• Manage and enhance Databricks environments, including clusters, workloads, SQL Warehouses, performance tuning, and cost optimization
• Administer and support Unity Catalog, data governance, security, lineage, and access controls
• Develop robust ingestion frameworks for structured, semi-structured, and unstructured data sources
• Implement monitoring, observability, automation, and operational best practices across the platform
• Drive Infrastructure-as-Code and CI/CD initiatives using Terraform, Azure DevOps, Git, and GitHub Actions
• Partner with architecture, security, governance, and business teams to deliver trusted enterprise data solutions
• Provide technical leadership and mentorship to engineering teams

? 5+ years of experience in Data Engineering, Data Platform Engineering, or Cloud Data Engineering

? Strong hands-on experience with:

• Databricks
• Spark/PySpark
• Delta Lake
• SQL
• Python
• Azure Data Factory
• Azure Data Lake Storage (ADLS Gen2)
• Unity Catalog

? Experience with:

• Collibra or similar data governance platforms
• Immuta or comparable data security and access management tools
• CI/CD, Infrastructure as Code, and cloud automation
• Data integration across APIs, databases, enterprise applications, and event-driven architectures

? Strong understanding of:

• Data governance
• Data security and privacy
• Role-Based and Attribute-Based Access Controls (RBAC/ABAC)
• Monitoring, observability, incident management, and platform operations

Nice to Have

• dbt
• Apache Airflow
• Azure Event Hubs
• Spark Structured Streaming
• Azure Synapse Analytics
• Microsoft Purview
• Kubernetes
• FinOps/Cloud Cost Optimization
• AI/ML Data Platform experience