Développeur(-euse) d’applications de veille stratégique, données et analyses
New
CanadaFull-TimeMiddle
Salary74,500 - 111,800 CAD per year
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Job Details
- Experience
- 5+ years of experience in business intelligence development, data analytics, reporting, or data warehouse environments.
- Required Skills
- PythonSQLBusiness IntelligenceGCPJavascriptBigQueryLooker
Requirements
- Bachelor’s or college degree in Information Technology, Computer Science, Data Analytics, Business Intelligence, or a related field, or equivalent experience.
- 5+ years of experience in business intelligence development, data analytics, reporting, or data warehouse environments.
- Strong expertise in SQL, including query writing, optimization, joins, aggregations, and data transformations.
- 3+ years of experience developing dashboards, reports, datasets, and visual analytics using enterprise BI tools.
- Solid understanding of data warehousing concepts, dimensional modeling, data governance, and data quality practices.
- Experience translating business requirements into scalable BI and analytics solutions.
- Familiarity with SDLC methodologies, including testing, documentation, deployment, and Agile or Waterfall frameworks.
- Experience with Google Cloud Platform, particularly BigQuery, is considered a strong asset.
- Exposure to BI tools such as MicroStrategy, Looker, or similar platforms is an asset.
- Knowledge of Python, JavaScript, AI tools, conversational analytics, or customer data platforms is an advantage.
Responsibilities
- Design, develop, test, deploy, and support business intelligence solutions, including dashboards, reports, semantic layers, and data models.
- Translate business requirements into scalable analytics and reporting solutions.
- Write, validate, optimize, and troubleshoot complex SQL and BigQuery queries.
- Develop and maintain BI components such as datasets, dashboards, visualizations, and semantic structures.
- Ensure adherence to performance, security, governance, and data quality standards.
- Execute testing, validation, and data reconciliation activities.
- Monitor, maintain, and improve BI and data environments.
- Collaborate with business, data engineering, infrastructure, and security teams.
- Identify and communicate risks, issues, and delays.
- Contribute to automation initiatives using Python, JavaScript, and AI-based solutions.
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