Instructor Data Engineering And Analytics Job In Vancouver

Job Description

• 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.

• 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 (including but not limited to) data integration, data management, data warehousing and reporting, and big data analytics.
• Experience with building predictive and prescriptive models in a business setting (i.e., regression, decision trees, deep learning etc.).

• Working knowledge of Learning Management System (LMS); Canvas, is an asset.
• Previous teaching experience at a college or a university level is an asset.
• Criminal background check will be required if selected.

• 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 D3.js.
• 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.

• 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.

• 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.

• 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.