Azure Databricks Engineer with Python

Role: Azure Databricks Engineer with Python & Spark (Senior / Lead)
Location: Weehawken, NJ (Onsite from Day 1)
Job Type: W2 Contract
Note: 2 positions are available - Senior & Lead
Experience
Level:
Senior
OR
Lead

Must Have Skills (Mandatory)

• Apache Spark
• Python
• Azure Data Factory
• Azure SQL Microsoft
• Azure Synapse Analytics
• ETL/ELT Solutions

Nice To Have Skills

• Apache Kafka
• CI/CD

Experience & Qualifications

• Expert level understanding of Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service
• Working knowledge of Python
• Expert level skills writing and optimizing complex SQL
• Experience with complex data modeling, ETL design, and using large databases in a business environment
• Experience with building data pipelines and applications to stream and process datasets at low latencies
• Fluent with Big Data technologies like Spark, Kafka and Hive
• Designing and building data pipelines using API ingestion and Streaming ingestion methods
• Knowledge of Dev-Ops processes (including CI/CD) and Infrastructure as code
• Experience in developing NoSQL solutions using Azure Cosmos DB
• Thorough understanding of Azure and AWS Cloud Infrastructure offerings

Key Responsibilities

• Design and implement scalable and secure data processing pipelines using Azure Data Factory, Azure Databricks, and other Azure services
• Manage and optimize data storage using Azure Data Lake Storage, Azure SQL Data Warehouse, and Azure Cosmos DB
• Monitor and troubleshoot data-related issues within the Azure environment to maintain high availability and performance
• Automate data pipelines and workflows to streamline data ingestion, processing, and distribution tasks
• Utilize Azure's analytics services, such as Azure Synapse Analytics, to provide insights and support data-driven decision-making
• Provide guidance and support for data governance, including metadata management, data lineage, and data cataloging

Note: Visa Independent candidates are highly preferred