What are the responsibilities and job description for the Azure Data Engineer with Databricks position at OmegaHires?
Certifications:
Azure Data Engineer Associate or Databricks certified Data Engineer Associate certification.
Requirements:
Strong expertise in Databricks (Delta Lake, Unity Catalog, Lakehouse Architecture, Table Triggers, Delta Live Pipelines, Databricks Runtime etc.)
Proficiency in Azure Cloud Services.
Solid Understanding of Spark and PySpark for big data processing.
Experience in relational databases.
Knowledge on Databricks Asset Bundles and GitLab.
Responsibilities:
Data Pipeline Development:
Build and maintain scalable ETL/ELT pipelines using Databricks.
Leverage PySpark/Spark and SQL to transform and process large datasets.
Integrate data from multiple sources including Azure Blob Storage, ADLS and other relational/non-relational systems.
Collaboration & Analysis:
Work Closely with multiple teams to prepare data for dashboard and BI Tools.
Collaborate with cross-functional teams to understand business requirements and deliver tailored data solutions.
Performance & Optimization:
Optimize Databricks workloads for cost efficiency and performance.
Monitor and troubleshoot data pipelines to ensure reliability and accuracy.
Governance & Security:
Implement and manage data security, access controls and governance standards using Unity Catalog.
Ensure compliance with organizational and regulatory data policies.
Deployment:
Leverage Databricks Asset Bundles for seamless deployment of Databricks jobs, notebooks and configurations across environments.
Manage version control for Databricks artifacts and collaborate with team to maintain development best practices.
Azure Data Engineer Associate or Databricks certified Data Engineer Associate certification.
Requirements:
Strong expertise in Databricks (Delta Lake, Unity Catalog, Lakehouse Architecture, Table Triggers, Delta Live Pipelines, Databricks Runtime etc.)
Proficiency in Azure Cloud Services.
Solid Understanding of Spark and PySpark for big data processing.
Experience in relational databases.
Knowledge on Databricks Asset Bundles and GitLab.
Responsibilities:
Data Pipeline Development:
Build and maintain scalable ETL/ELT pipelines using Databricks.
Leverage PySpark/Spark and SQL to transform and process large datasets.
Integrate data from multiple sources including Azure Blob Storage, ADLS and other relational/non-relational systems.
Collaboration & Analysis:
Work Closely with multiple teams to prepare data for dashboard and BI Tools.
Collaborate with cross-functional teams to understand business requirements and deliver tailored data solutions.
Performance & Optimization:
Optimize Databricks workloads for cost efficiency and performance.
Monitor and troubleshoot data pipelines to ensure reliability and accuracy.
Governance & Security:
Implement and manage data security, access controls and governance standards using Unity Catalog.
Ensure compliance with organizational and regulatory data policies.
Deployment:
Leverage Databricks Asset Bundles for seamless deployment of Databricks jobs, notebooks and configurations across environments.
Manage version control for Databricks artifacts and collaborate with team to maintain development best practices.
