Position: AZURE CLOUD DATA PLATFORM ENGINEER

Duration: 06+ Months

Location: Dallas, TX or Richmond VA (Hybrid)

Visa: Citizen, GC,

JOB Description

Data and Analytics team

They’ve been in Azure for a while, building out a data ecosystem into Azure

Snowflake is new, ingests data into ADF

Skillsets:

Azure/Azure data factory

Storage accounts

Familiar with infrastructure as code (They use bicep but terraform experience is ok)

Devops pipeline to deploy code to infrastructure

Experience supporting team with troubleshooting / solving problems and escalating if need be

Python for data engineering for workflows and pipelines

Just migrated into snowflake, familiarity, just migrated to it

Automation, enterprise environment

What he doesn’t want to see:

Don’t need database experience

Stay away from data engineers as this person won’t create ETL pipelines

With candidates, dig into data resources/functions, doesn’t want to see just pure infrastructure or networking

Job Description:

The Data and Analytics Engineering - Platform team is critical to making our organization's data strategy successful. You will play a key role in building and managing modern, adaptive, data-driven, and secure platforms and processes to enable Data & Analytics Engineering. You should have strong fundamentals of Data/Software Engineering, DevOps, and hands-on experience with Azure Cloud services. You will work on cross-functional initiatives and projects.  

Roles and Responsibilities: 

Build, deploy, and configure Azure infrastructure, including but not limited to Azure Data Factory, storage, key vaults, virtual networking, virtual machines, and automated deployments 

Automate infrastructure deployment through Infrastructure as Code and CI/CD pipelines 

Evaluate and automate the scaling and capacity requirements within Azure environment 

Implement, setup, configure, monitor, and maintain cloud based Data & Analytics platforms such as Databricks and Snowflake. Troubleshoot and resolve environment performance issues, connectivity issues, security issues 

Make recommendations and execute cost saving strategies for Cloud services 

Self-directed and able to balance the priorities of multiple teams, systems, and products with a leadership mindset 

Work collaboratively in teams and develop meaningful relationships to achieve common goals 

Streamline development and operation processes via continuous integration, deployment, automated testing while leveraging SRE principles 

Drive efficient resolution for system outages as well as performance and functional shortcomings. Engage in critical support situations and effectively, efficiently, and quickly drive successful resolution 

Design and implement solutions that leverage cloud services such as serverless computing, containers, and data lakes.