Full-Time Big Data Engineer

IMPORTANT NOTES:

• This position will be fully remote. Candidates must be living and working within the continental US and would be expected to work the client's standard Central Time Zone business hours.
• This position is expected to work 35 hours per week.

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 NDUS's needs.
• Maintain and enhance existing big data infrastructures to meet NDUS's 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 NDUS's 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 NDUS's 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.

SkillRequired / DesiredAmountof ExperienceIaaS, PaaS, or SaaS data or AI implementations within Microsoft AzureRequired3YearsExploratory Data Analysis (EDA): Proficiency in EDA techniques to support ETL/ELT processesRequired3YearsImplementation of Development and Production Workflows in Azure Data Factory and DatabricksRequired2YearsStrong scripting skills in Python and SQLRequired3YearsExpert proficiency of data engineering creation in Microsoft FabricRequired1YearsExpert proficiency with Excel and Power BIHighly desired2YearsExpert proficiency of Delta Lake format and protocolHighly desired1YearsExpert understanding of the Data Lakehouse Medallion ArchitectureHighly desired1Years