Data Engineer - Hybrid - 80% remote

Wake County Government•Raleigh, NC

4d•Hybrid

About The Position

Calling all experienced Data Engineers! Bring your expertise to this exciting hybrid role and help turn complex data into solutions that help drive decisions while enjoying 80% remote work and requires the ability to report onsite to the Raleigh, NC office within two hours. As the Data Engineer you will develop and maintain operationalized data pipelines for data science and data analysis. You will work closely with departmental business analysts and subject matter experts to understand the requirements and translate that into an automated and optimized data model. You will also serve as an evangelist for data governance, security, and storage best practices, learning and using modern data preparation, integration, and AI-enabled metadata management tools and techniques.

Requirements

Bachelor's degree in Computer Science, Information Systems, Computer Engineering or a related field
Two years of experience in data science and analytics
Six years of experience in data science or analytics may be substituted for the combined education and experience requirements
Equivalent education and experience are accepted
Solid experience with SQL and relational database technologies, including developing, troubleshooting and optimizing queries, stored procedures, and data transformations
Experience with scripting or programming languages such as Python, PowerShell, Java, or similar languages used for data processing and automation

Nice To Haves

Experience developing and supporting production data pipelines, including monitoring, error handling, scheduling, documentation and data quality validation
Experience with data integration, ETL/ELT and automation tools such as Boomi, Azure Data Factory, or similar platforms
Experience and knowledge of data management, data quality, performance optimization and data governance best practices
Knowledge of data visualization and business intelligence platforms such as Power BI, Tableau, Qlik, or similar tools, with an understanding of how engineered data supports downstream analytics and reporting
Knowledge of scripting, data preparation and automation tools such as Python, Alteryx, KNIME, or similar technologies
Knowledge of data governance, data quality, data classification, security and access control requirements as they apply to production data pipelines and integrations
Ability to communicate and collaborate effectively with business subject matter experts, technical teams and organizational leadership
Ability to communicate technical information clearly in written and verbal formats and translate business needs into technical specifications for data solutions

Responsibilities

Developing and maintaining operationalized data pipelines for data science and data analysis
Working closely with departmental business analysts and subject matter experts to understand the requirements and translate that into an automated and optimized data model
Evangelist for data governance, security and storage best practices
Learning and using modern data preparation, integration and AI-enabled metadata management tools and techniques