Saransh Inc
Azure Databricks Engineer with Python & Spark - 2 Positions (Senior & Lead) - On
Saransh Inc, Weehawken, New Jersey, United States
Azure Databricks Engineer with Python & Spark - 2 Positions (Senior & Lead) - Only W2
5 days ago Be among the first 25 applicants
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
#J-18808-Ljbffr
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
#J-18808-Ljbffr