Cloud Data Strategist

3 days ago

Mumbai, Maharashtra, India beBeeData Full time ₹ 75,00,000 - ₹ 1,25,00,000
Job Title:

Cloud Data Architect

Job Summary:

As a Cloud Data Architect, you will design and develop scalable data pipelines using Azure Databricks and ADF. You will administer Databricks environments, including user access, clusters, and Unity Catalog for data lineage, governance, and security.

Key Responsibilities:
  • Design, develop, and optimize scalable data pipelines using Azure Databricks and ADF.
  • Administer Databricks environments, including user access, clusters, and Unity Catalog for data lineage, governance, and security.
  • Support the deployment, scheduling, and monitoring of data workflows and jobs in Databricks and ADF.
  • Implement best practices for CI/CD, version control, and operational monitoring for pipeline deployments.
  • Implement and manage Delta Lake to ensure reliable, performant, and ACID-compliant data operations.
Requirements:
  • Apollo Spark (on Databricks)
  • Proficient in PySpark and spark SQL
  • Spark optimization techniques (caching, partitioning, broadcast joins)
  • Writing and scheduling notebooks/jobs in Databricks
  • Understanding of Delta Lake architecture and features
  • Working with Databricks Workflows (pipelines and job orchestration)
  • SQL/Python Programming
  • Handling JSON, XML, and other semi-structured formats
  • Experience with API integration using requests, http, etc.
  • Error handling and logging
API Ingestion:
  • Designing and implementing ingestion pipelines for RESTful API
  • Transforming and loading JSON responses to Spark tables
Cloud & Data Platform Skills:
  • Databricks on Azure
  • Cluster configuration and management
  • Unity Catalog features
  • Azure Data Factory
  • Creating and managing pipelines for orchestration
  • Linked services and datasets for ADLS, Databricks, SQL Server
  • Parameterized and dynamic ADF pipelines
  • Triggering Databricks notebooks from ADF
Data Engineering Foundations:
  • Data modeling and warehousing concepts
  • ETL/ELT design patterns
  • Data validation and quality checks
  • Working with structured and semi-structured data (JSON, Parquet, Avro)
DevOps & CI/CD:
  • Git/GitHub for version control
  • CI/CD using Azure DevOps or GitHub Actions for Databricks jobs
  • Infrastructure-as-code (Terraform for Databricks or ADF)

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