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Data Engineering and Analytics Instructor

2 months ago

Vancouver, British Columbia, Canada Canadian College of Technology and Business Full time
Job Title:

Data Engineering and Analytics Instructor

Job Summary:

The Canadian College of Technology and Business is seeking an experienced professional to teach a module in the Data Engineering and Analytics Diploma Program. As an Instructor, you will be responsible for cultivating an immersive learning environment, designing and implementing dynamic learning experiences, and facilitating engaging class discussions.

Responsibilities:
  • Cultivate an immersive learning environment tailored for post-secondary students, fostering engagement and active participation.
  • Design and implement dynamic learning experiences leveraging available resources, integrating diverse teaching methodologies to achieve course objectives effectively.
  • Streamline lesson planning, assignments, and class activities, ensuring alignment with course objectives and institutional standards.
  • Facilitate engaging class discussions to stimulate collaboration, communication, and critical thinking among students.
  • Encourage intellectual exploration, guiding students to hone their analytical and reasoning skills.
  • Spearhead the exploration and application of market-leading technologies and lead students in research and development projects.
  • Provide personalized academic support through tutoring and counseling, offering constructive feedback and motivation as needed.
  • Extend academic assistance beyond the classroom through scheduled office hours, email correspondence, and group study sessions.
  • Actively contribute to departmental and faculty meetings, staying abreast of relevant developments and responsibilities.
  • Pursue ongoing research endeavors within the field, deepening expertise and enhancing teaching efficacy.
Requirements:
  • A certificate, diploma, or post-secondary degree relevant to the subject matter and two years of full-time work experience in a career occupation relevant to the subject matter of the course, or
  • 10 years of full-time work experience in a career occupation relevant to the subject matter of the program.
  • A master's degree in science or in an appropriate discipline is considered an asset.
  • Experience in data integration, data management, data warehousing, and reporting, and big data analytics.
  • Experience with building predictive and prescriptive models in a business setting.
  • Working knowledge of Learning Management System (LMS); Canvas is an asset.
  • Previous teaching experience at a college or university level is an asset.
  • Criminal background check will be required if selected.
Knowledge and Skills:Data Analysis:
  • Proficiency in statistical methods and tests (t-tests, chi-square tests, ANOVA).
  • Understanding of distributions, hypothesis testing, and probability.
  • Proficiency with tools like Tableau, Power BI, and.
  • Ability to create effective and visually appealing data visualizations.
  • Strong SQL skills for data extraction and manipulation.
  • Experience with query optimization and complex joins.
  • Proficiency in Python or R for data manipulation and analysis.
  • Knowledge of data analysis libraries such as pandas, NumPy, and ggplot2.
  • Techniques for handling missing data, outliers, and ensuring data quality.
  • Data wrangling and transformation using tools like Excel, OpenRefine, or Python/R libraries.
  • Ability to translate business requirements into data-driven solutions.
  • Strong analytical skills to interpret data and generate insights.
AI and Machine Learning:
  • Familiarity with supervised and unsupervised learning techniques.
  • Basic implementation of regression, classification, and clustering algorithms using Python/R.
  • Techniques for feature engineering, normalization, and data transformation.
  • Handling imbalanced datasets and performing cross-validation.
  • Understanding of evaluation metrics like accuracy, precision, recall, F1 score.
  • Basic hyperparameter tuning and model validation techniques.
Data Engineering:
  • Expertise in relational databases (MySQL, PostgreSQL) and NoSQL databases (MongoDB, Cassandra).
  • Advanced SQL for complex queries, indexing, and performance tuning.
  • Designing and implementing robust ETL pipelines.
  • Proficiency with ETL tools such as Apache NiFi, Talend, Informatica.
  • Proficiency in Hadoop, Spark, Kafka, and other big data frameworks.
  • Understanding of distributed computing and data processing.
  • Strong skills in Python, Java, and SQL.
  • Scripting with Bash or other shell languages for automation.
  • Experience with AWS (Redshift, S3), Azure (Data Lake, Synapse), Google Cloud (BigQuery).
  • Familiarity with cloud data services and infrastructure management.
  • Designing and implementing data models for efficient storage and retrieval.
  • Understanding of data warehousing and data lakes.
  • Knowledge of system design principles and best practices for scalability and reliability.
  • Experience with microservices architecture and API development.
  • Implementing data security measures and ensuring compliance with regulations.
  • Knowledge of encryption, masking, and data governance.
  • Proficiency in administering enterprise Linux environments.
Teaching and Program Development:
  • Previous curriculum and program development experience is considered an asset.
  • Proven experience supervising students, providing support and feedback in constructive and meaningful manners is highly desirable.
  • Excellent written and oral communication skills.
  • Ability to communicate complex information to students both orally and written in an understandable manner.
  • Demonstrate a commitment to diversity, equity, and inclusion when interacting with students and colleagues.
  • Capable of working independently as well as being part of a team.
  • Being able to work under pressure/fast-paced environment and deliver on scheduled deadlines.

We are an Equal Opportunity Employer and do not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity and/or expression, status as a veteran, and basis of disability or any other federal, provincial, or local protected class.