Data Modeler

Primary Work: Serve as Data Engineer for the Data & Analytics (D&A) Office. Education: Bachelor's or master's degree in Data Science, Computer Science, Information Systems or other Information Technology major, or equivalent work experience. Required Tasks to be performed: Design, implement, and maintain robust data pipelines and architectures. Develop and implement data quality control procedures to ensure the accuracy, completeness, and consistency of data assets. Optimize data processing workflows and algorithms for efficiency, scalability, and reliability. Perform ad hoc data cleansing of datasets as needed. Configure SAS Viya analytics platform. Ensure compliance with data privacy regulations and security best practices in data handling, storage, and transmission. Stay current with emerging technologies, tools, and methodologies in data engineering and environmental science. Collaborate with data scientists and analysts to optimize models and algorithms for data quality, security, and governance. Monitor and tune data systems, identify and resolve performance bottlenecks, and implement caching and indexing strategies to enhance query performance. Transform raw data into a usable format by applying data cleansing, aggregation, filtering, and enrichment techniques. Establish the governance of data and algorithms used for analysis, analytical applications, and automated decision making. Provide leadership, guidance, and mentorship to junior staff members and colleagues, fostering a culture of continuous learning, innovation, and excellence in D&A practices. Required Knowledge, Skills & Abilities (KSAs): 3-5 years' experience in data engineering, including designing and implementing data pipelines and ETL processes. Proficiency with data management platforms such as SAS Viya, Alteryx, or others. (Proficiency level 4) Proficiency in programming languages such as Python, SQL, or Java. (Proficiency level 4) Strong analytical and problem-solving skills, with the ability to analyze complex datasets and extract actionable insights. (Proficiency level 4) Knowledge of relational database design and data modeling. (Proficiency level 4) Ability to establish and maintain effective working relationships with others. (Proficiency level 3) Ability to work independently. (Proficiency level 3) Ability to determine work priorities and ensure proper completion of work assignments. (Proficiency level 3) Ability to communicate effectively, both verbally and in writing. (Proficiency level 3) Preferred Knowledge, Skills & Abilities (KSAs): Familiarity with environmental science, water quality, or related fields. Experience with implementing data warehouses, data lakes, or data lakehouses. Experience with cloud computing platforms such as Azure. Experience with business intelligence tools such as Qlik Sense.