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Primary responsibilities:

- Design and implement robust dimensional and relational data models that support analytical use cases for organizations across the business
- Build and maintain scalable dbt transformation pipelines, ensuring high data quality, performance, and cost-efficiency from raw ingestion to business-ready outputs
- Own the transformation and modeling of curated (Silver/Gold) datasets, ensuring transparent contracts and traceability from raw to business-ready data.
- Collaborate with data analysts, product analytics, data scientists, and business stakeholders to translate requirements into durable data products that support experimentation, A/B testing, and advanced analytics
- Implement data quality tests, monitoring, SLAs, and alerting to ensure reliability of critical analytical datasets
- Partner with Data Engineers to define and enforce data contracts, ensuring schema stability and minimizing downstream breakage
- Follow analytics engineering best practices including version control, testing standards, and documentation
- Empower self-service analytics by building intuitive, well-documented data marts and semantic layers.
- Minimum 5+ years of experience in analytics engineering, data modeling, or similar roles working with enterprise-scale data, and demonstrated ownership of data products and cross-functional collaboration




- Expert-level SQL skills with deep understanding of query optimization and performance tuning
- Extensive experience with dbt (data build tool) including testing, documentation, and package management
- Strong programming skills in Python for data manipulation, automation, and custom analytics workflows
- Strong understanding of dimensional modeling, star schemas, one big table, and other data modeling methodologies
- Experience with modern cloud data warehouses (Snowflake, Big Query, Redshift, or Databricks)
- Familiarity with orchestration frameworks (Airflow) and how analytics transformations are scheduled within broader data workflows
- Experience working with version control systems (Git) and implementing CI/CD for analytics code
- Strong business acumen and ability to translate business requirements into well-designed data models
- Understanding of data governance, privacy, and compliance requirements (GDPR, CCPA, and SOX)
- Familiarity with BI tools (Tableau, Looker, Mode, or similar) and how analysts consume data
- Strong ownership mindset with a passion for deeply understanding ambiguous business problems and translating them into clean, maintainable, and well-tested data models.
- Excellent communication skills with ability to explain technical concepts to both technical and non-technical audiences
- Dedication to data quality, documentation, and empowering others through self-service analytics

Apply on Kit Job: kitjob.ca/job/2fss3w

📌 Sr. Data Analytics Engineer (Canada)
🏢 Mastech Digital
📍 Canada