• Develop and maintain scalable data pipelines, automating data flows and ensuring efficient data transfer between
systems.
• Create and maintain data connectors via APIs, enabling seamless integration across various data sources.
• Manage and optimize Google BigQuery for data warehousing, ensuring the quality and integrity of data from
capture to reporting.
• Leverage technologies such as Python, R, Airflow, and dbt for data orchestration, analysis and automation.
• Collaborate with cross-functional teams, including IT, Digital Learning, and divisional teams, to streamline processes
and establish data management best practices.
• Assist with the development of interactive data dashboards in Looker Studio and other visualization tools, providing
insights for faculty, staff, and management.
• Design and implement data visualizations, ensuring adequate, accurate, and legitimate data collection techniques.
• Maintain updated documentation and manage change processes for data systems, adhering to data governance
standards.
• Stay updated with the latest technological trends in educational software and data systems, recommending and
adapting new solutions.
• Serve as the main point of contact between data owners, identifying data issues, and providing technological
solutions.
• Assist in project management, including formulating strategies for effective data use and producing knowledge
base and training materials.
Qualifications
• Degree in Computer Science, Data Science, Data Engineering, or a related field, with relevant certifications.
• At least two years of experience in data automation and engineering, with a portfolio that includes academic
projects or work.
• Proficiency in data engineering and automation technologies, including advanced SQL, JavaScript, CSS, HTML, and
version control systems like Github or SVN.
• Experience with data visualization tools like Looker Studio and data warehousing tools such as BigQuery.
• Understanding of various database types (Relational, NoSQL, etc.), and OLAP/OLTP systems.
• Familiarity with machine learning and predictive analytics is highly desirable.
• Strong analytical skills, with the ability to resolve technical issues systematically.
• Excellent verbal and written communication skills, with a positive and growth mindset.
• Ability to work independently, maintain confidentiality, and manage time effectively.
Contacts
• Students, Staff and Vendors
Working Conditions
• School Environment
• Working hours 8am to 5pm, Monday to Friday
