Consultant, Data & Analytics - New Grad (May 2026)

BDO•Edmonton, AB

1d•Hybrid

About The Position

BDO Digital is looking for a Data Analytics/Data Engineer New Grad to join our growing client-facing team on a full-time permanent basis. This is a net new role where responsibilities will include playing an integral role in our delivery practice as we execute on enterprise-level client engagements through our various industry specializations. You will engage directly with clients, drive the implementation and successful end-user experience of analytics solutions, and execute on engagements. You will collaborate with the client and delivery team to ensure that any applicable milestones and deliverables are met on time and on budget. Responsibilities also include designing and developing industry-specific data models for client projects in industries such as Natural Resources, Finance, Manufacturing and Distribution, and Retail. You will work with other engineers to enhance data models and improve data query efficiency, and create complex data queries to facilitate ad hoc and exploratory analytics. Additionally, you will build real-time data capture and transformation functionality across all products and build out the technology stack for Business Intelligence and Data Warehouse. You will be responsible for cleaning data by reviewing for data inconsistencies and identifying opportunities to improve the data collection process. You will also wrangle/munge data, transforming or mapping data from one raw data form into another format with the intent of making it more appropriate and valuable for analytics. You will develop, construct, test, and maintain architectures such as databases and large-scale data processing systems, and design, construct, install, test, and maintain highly scalable data management systems. You will employ a variety of languages and tools (e.g., scripting languages) to marry systems together. You will build or recommend data visualization tools and business intelligence tools such as interactive dashboards and automated reports, to enable leaders to make swift, fact-based decisions. Finally, you will remain up-to-date with development technologies, both current and future, in order to deliver state-of-the-art Analytics solutions for our customers.

Requirements

Post-secondary education in engineering or computer science or equivalent work experience
Good experience working with Azure Databricks, Azure Data Factory and Azure Data Lake
Programming experience in Python
Strong attention to the quality of work delivered (attention to detail)
Able to adapt quickly to changing client requirements

Nice To Haves

Experience using the Apache Hadoop ecosystem (Spark, Data Lake, Hive, HDFS, Impala) to tackle "big data" problems
Knowledge of ETL, ELT, Lambda and Kappa data architectures
Experience with the Microsoft SQL Server Analytics stack including: Core SQL, SSIS, SSRS, SSAS
Experience working with SQL and NoSQL databases
Knowledge of Continuous Integration and Source Control systems (e.g. Gradle, Maven, Bamboo, TeamCity, Git)
Data Visualization experience in Power BI, Tableau, or similar
Exposure to data science, machine learning or statistics
Some experience using Docker

Responsibilities

Play an integral role in our delivery practice as we execute on enterprise level client engagements through our various industry specializations
Engage directly with clients and drive the implementation and successful end user experience of analytics solutions; execute on engagements and collaborate with the client and delivery team to ensure that any applicable milestones and deliverables are met on time and on budget
Design and develop industry-specific data models for client projects in industries such as Natural Resources, Finance, Manufacturing and Distribution, and Retail
Work with other engineers to enhance data models and improve data query efficiency; create complex data queries to facilitate ad hoc and exploratory analytics
Build real-time data capture and transformation functionality across all products and build out technology stack for Business Intelligence and Data Warehouse
Clean data: review for data inconsistencies and identify opportunities to improve data collection process
Wrangle/Munge data: transform or map data from one raw data form into another format with the intent of making it more appropriate and valuable for analytics
Develop, construct, test and maintain architectures such as databases and large-scale data processing systems; design, construct, install, test and maintain highly scalable data management systems
Employ a variety of languages and tools (e.g. scripting languages) to marry systems together
Build or recommend data visualization tools and business intelligence tools such as interactive dashboards and automated reports, to enable leaders to make swift, fact-based decisions
Remain up to date of development technologies, both current and future in order to deliver state-of-the-art Analytics solutions for our customers