Job Opportunity: Azure Data Engineer - Raleigh, NC - 12 Months with possible extensions

[Venu Goud]

 

Job Title: Azure Data Engineer

Location: Raleigh, NC

Duration: 12 Months with possible extensions

Looking for H4(E.A.D)

Send me the resume to Venu.e...@Infosharesystems.com

 

Main skill: Data Software Engineering

Skill Specification: DSE Python Azure Databricks

 

Must have skills:  Apache Spark, Azure Data Factory, Azure SQL Microsoft, Azure Synapse Analytics, ETL/ELT Solutions

 

Nice to have skills: Apache Kafka, CI/CD, Python

 

Job Description:

Do you want to design and build next generation business applications using the latest technologies? Are you confident at iteratively refining user requirements and removing any ambiguity? Do you like to be challenged and encouraged to learn and grow professionally?

 

Your Expertise:

• 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.
• Expert level understanding of Azure Data Factory, Azure Synapse, Azure SQL, Azure Data Lake, and Azure App Service.
• 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.
• Working knowledge of Python is desirable.

 

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.
• Implement data security measures, including encryption, access controls, and auditing, to protect sensitive information.
• 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.
• Document data procedures, systems, and architectures to maintain clarity and ensure compliance with regulatory standards.
• Provide guidance and support for data governance, including metadata management, data lineage, and data cataloguing.