Azure Big Data Engineer

Title: Azure Big Data Engineer

Location: Remote

Length: Long term

Restriction: W2 or C2C

Description:

Interview Type: Webcam Interview *** Very long term project initial PO for 1 year, expect to go for 4+ years *** *** Remote *** 35 hours per week

Short Description:

Develops, engineers, maintains, runs tests, evaluates, and implements big data infrastructure, projects, tools, and solutions, working with the latest database technologies, to get results from vast amounts of data quickly.

Job Description:

The Big Data Engineer is a vital member of a collaborative team, responsible for designing, engineering, maintaining, testing, evaluating, and implementing big data infrastructure, tools, projects, and solutions for the North Dakota University System (NDUS).This role involves working closely with the team to leverage cutting edge database technologies for the swift retrieval of results from vast datasets. The engineer will select and integrate big data frameworks and tools to meet specific needs and manage the entire lifecycle of large datasets to extract valuable insights.

Key Responsibilities:

Design and implement scalable big data solutions tailored to NDUSs needs.

Maintain and enhance existing big data infrastructures to meet NDUSs unique requirements.

Test and evaluate new big data technologies and frameworks for compatibility with NDUS systems and goals.

Collect, store, process, manage, analyze, and visualize large datasets to derive actionable insights.

Collaborate with team members to integrate big data solutions with existing NDUS systems.

Ensure data integrity and security across all platforms used within NDUS.

Develop and optimize data pipelines for ETL/ELT processes specific to NDUSs data needs.

Document technical solutions and maintain comprehensive records in line with NDUS standards and protocols.

Stay updated with the latest trends and advancements in big data technology relevant to NDUSs strategic initiatives.

Required Qualifications:

Thorough understanding of cloud computing technologies, including IaaS, PaaS, and SaaS implementations.

Skilled in exploratory data analysis (EDA) to support ETL/ELT processes.

Proficiency with Microsoft cloud products, including Azure and Fabric.

Experience with tools such as Data Factory and Databricks.

Ability to script in multiple languages, with a strong emphasis on Python and SQL.

Preferred Qualifications:

Experience with data visualization tools.

Proficiency with Excel and Power BI.

Familiarity with Delta Lake.

Knowledge of Lakehouse Medallion Architecture.

Required Skills:

IaaS, PaaS, or SaaS data or AI implementations within Microsoft Azure 3 Years

Exploratory Data Analysis (EDA): Proficiency in EDA techniques to support ETL/ELT processes 3 Years

Implementation of Development and Production Workflows in Azure Data Factory and Databricks 2 Years

Strong scripting skills in Python and SQL 3 Years

Expert proficiency of data engineering creation in Microsoft Fabric 1 Years

Expert proficiency with Excel and Power BI 2 Years

Expert proficiency of Delta Lake format and protocol 1 Years

Expert understanding of the Data Lakehouse Medallion Architecture 1 Years preferred