Analytics Full Stack Engineer

Description:

Reporting to the Manager, Data & Analytics Engineering, the Analytics Full Stack Engineer is responsible for the design, development, and implementation of the end-to-end full stack of data and analytics, including data engineering, analytics/dataset engineering, BI engineering, data science and machine learning engineering, and data platform engineering. The Analytics Full Stack Engineer drives data modernization, analytics solutions, machine learning models, and innovation for BCI.

The Analytics Full Stack Engineer works closely with internal team members, such as the Data Product Manager and Data Governance Lead, and collaborates with the business and technology teams.

This position can be based in either Vancouver or Victoria with some travel between the two offices.

WHAT YOU BRING

• Bachelor’s or Master’s degree in Big Data/Data Science, Science, Technology, Engineering, Mathematics, or a related field

• A minimum of 5 years of experience as a Data Engineer, Analytics Engineer, Data Scientist, BI Engineer, or Analytics Full Stack Engineer

• Experience gathering business requirements, conducting business analysis, and solution design for end-to-end data solutions (e.g. data ingestion, reusable datasets, analytics solutions, ML models)

• Experience with cloud-based data warehouse, data lake, and data lakehouse design, development and sustainment

• Coding skills and deep proficiency with SQL, Python/R, DAX, and Power Query

• Experience in database management and data processing performance optimization

• Experience in data modeling (e.g. star, snowflake, denormalized designs), data architecture and data structures

• Experience with training, developing, and productionizing statistical, machine learning and other data science models and utilizing data science platforms (e.g. Databricks, Azure ML)

• Must be proficient with wireframing, designing complex data visualization solutions, whilst taking into account solution user experience, and developing analytics solutions using modern data visualizaiton tools (e.g. Power BI, Tableau)

• Experience developing low-code/no-code applications and workflows (e.g. PowerApps, Power Automate)

• Experience administering and configuring cloud and on-premise data and analytics platforms

• Experience with scripting, version control systems (e.g. Git), cloud platforms, Agile and DevOps, including CI/CD technologies and practices

• Must have excellent listening, communication, collaboration and problem-solving skills

• Knowledge of the Azure cloud fundamentals, M365, and Azure data analytics and Power Platform stack is an asset (e.g. Azure Data Factory, Azure Data Lake Store, Azure SQL MI/DB, Azure Synapse, Power BI/Power Apps/Power Automate, Azure ML, Azure Databricks, Microsoft Fabric)

• Knowledge or experience in master data management is an asset.

• Knowledge of the data opportunities within the investment management industry is an asset