Senior Data and Business Intelligence Engineer (Contract)
About the job
Job Title: Senior Data and Business Intelligence Engineer
Type of Position: 12-month contract
Reports to: Senior Manager, IT Solution Architecture & Application Development
Job Summary
With a thorough understanding of all aspects of the Brink's Canada business, the Senior Data and Business Intelligence Engineer is a key contributor to the design and execution of Brink's Canada data management strategy, business intelligence and analytical solutions roadmap, and AI Implementation. Working with each business unit, this role will identify and capture opportunities for enhancements, supporting continuous improvement and delivery of the company's strategic goals.
Also accountable for supporting new data requirements from the business and projects, this position serves as the liaison between the business subject matter experts and the technology teams, contributing to data gathering and cleansing automation, and any future BI requirements leveraging the Canadian Data Warehouse. The structure and discipline of Customer Master Data and BI tools that drive business value across all business units, are key to the success of the position.
Key Responsibilities
Collaborate with the business and technology project teams to determine data requirements and document business rules, workflow, objectives, and business value; build data models to organize important data for different teams across the business; data monitoring, cleansing, and updating.
Collaborate with the business to analyze current operational processes and data points, identify problems and propose opportunities for improvement to minimize risk and maximize efficiencies, and align with Brink's Canada strategic priorities
Produce detailed description of user needs and data requirements using an appropriate combination of narrative, use cases and flowcharts, translating business data requirements to IT functional specifications and test scenarios/scripts required
Support technical engagement with external partners, as required, collaborating to produce designs that meet the Global and Canadian business and technology requirements
Contribute to the creation of BI Dashboards based on requirements, working with each business area to launch and adopt BI as a key contributor for business making decisions; extract valuable insights from company data using SQL language, analyzing data, as well as creating data models.
Maintain an effective user-support relationship
Communicate with management and executives regarding status, milestones, and deliverables of IT projects.
Key Qualifications:
Educational Background: Bachelor's / Master degree in a quantitative field such as statistics, mathematics, computer science.
Experience: 5 to 10 years of experience in the field.
Technical Proficiency (Must Have): Proficiency in programming languages like SQL for querying databases, Power BI
Reporting (design and deployment), MS Excel advanced programming
Additional Proficiency: Python or R, DAX programming
Analytical Skills: Strong analytical and problem-solving skills.
Communication Skills: Excellent communication and presentation skills.
Additional Expertise: Experience with data visualization tools like Tableau or Power BI highly recommended.
Additional Requirements (Preferred)
Professional Certifications: Certifications such as the Google Data Analytics Professional Certificate or Microsoft
Certified Data Analyst Associate.
Industry-Specific Experience: Experience in specific industries, such as logistics, finance, is highly advantageous.
Capability to tailor data analysis to unique business contexts and challenges.
Essential Data Analyst Skills
Data Cleaning and Preparation: essential in any data analysis process: rectifying errors, resolving inconsistencies, and filling in missing values to ensure the data's accuracy and reliability.
Statistical Analysis: use statistical methods to uncover patterns, trends, and relationships in data, use of techniques like hypothesis testing to evaluate if observed effect is statistically significant or irrelevant.
Programming (e.g., Python, R): not mandatory, but appreciated.
Database Management: query and retrieve data using SQL is essential, understanding database structures and writing efficient queries.
Data Visualization Tools (e.g., Tableau, Power BI): create interactive charts, graphs, and dashboards that make complex data easy to understand and interpret.
Machine Learning Basics: understanding of machine learning is advantageous, predictive modeling and pattern