This is 100% onsite work position based in Tallahassee,FL. Apply only if you are willing to relocate.
Education: Bachelor's Degree in a field of study related to technology or finance. Work experience can substitute on a year for year basis for the degree.
Certifications: in the field preferred
Required Experience:
1. Experience in data engineering, including designing and implementing data pipelines and ETL
2. processes. (Proficiency level – 4)
3. Proficiency in programming languages such as Python and SQL. (Proficiency level – 3)
Experience with Alteryx Designer.
4. Experience with business intelligence tools such as Qlik Sense.
5. Familiarity with environmental science, water quality, or related fields.
6. Strong analytical and problem-solving skills, with the ability to analyze complex datasets and extract actionable insights. (Proficiency level – 4)
7. Knowledge of relational database design and data modeling. (Proficiency level – 3)
8. Experience with implementing data warehouses, data lakes, or data lakehouses. (Proficiency level – 3)
9. Ability to establish and maintain effective working relationships with others. (Proficiency level – 3)
1. Ability to work independently. (Proficiency level – 3)
1. Ability to determine work priorities and ensure proper completion of work assignments. (Proficiency level – 4)
1. Ability to communicate effectively, both verbally and in writing. (Proficiency level – 3)
Responsibilities:
• Design, implement, and maintain robust data pipelines and architectures in Alteryx Designer.
• Create and maintain logical data models in Oracle SQL Developer Data Modeler.
• Read, write, and update data.
• Create and maintain ETL code repository.
• Perform ad hoc data cleansing of data sets as needed.
Develop and implement data quality control procedures to ensure the accuracy, completeness, and consistency of environmental data.
• Define data quality standards and metrics.
• Execute procedures to monitor data quality.
• Identify data issues and propose remediation plans.
• Optimize data processing workflows and algorithms for efficiency, scalability, and reliability.
• 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
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