2 results for Database Manager in Toronto, ON

Data Engineer

Guelph, ON
onsite
Permanent
90000 - 110000 CAD / Yearly
Robert Half is looking to hire a Data Engineer for a current opening with an organization that is rapidly expanding. Please take a look at the summarized information below and apply if you are a good fit! Role: Data EngineerLocation: KW RegionIndustry: ConfidentialCompensation: $90k to $110k + Bonus + Vacation / PTO + Strong Benefits + Great work culture!Requirements:• Data engineering and pipelines: Hands-on experience with Microsoft Fabric, Lakehouse, Data Factory, Dataflows Gen2, notebook development, enterprise data integration, pipeline orchestration, and cloud-based analytics architectures. • SQL and data modelling: Proficiency in data transformation, dimensional models, KPI implementation, curated datasets, performance tuning, and optimization. • Python-based development: Utilization of Python for data processing, workflow automation, validation, quality controls, and operational data engineering. • Reporting and governance enablement: Support for Power BI semantic models, curated datasets, data governance, lineage, operational documentation, and reliable and auditable data operations. • Strategic fit: Alignment with enterprise reporting modernization, Microsoft Fabric expansion, and stronger data governance and analytics capabilities.
2026-08-20T00:00:00Z

Data Scientist

North York, ON
onsite
Permanent
100000 - 115000 CAD / Yearly
This job posting is for a current vacancy with our client. We are seeking an experienced Data Scientist for our client's growing Analytics team. The Data Scientist will be based in Toronto, Ontario, where they will turn complex data into practical insights that support business decisions. A core focus of this role includes machine learning expertise, data engineering capability, and analytical thinking to develop scalable solutions in a Databricks environment. You will work closely with technical and business teams to build reliable models, improve data workflows, and communicate findings in a clear and meaningful way. Key Responsibilities:• Develop, implement, and operationalize machine learning models and analytical solutions within Databricks to address business needs.• Create and support scalable data pipelines using Apache Spark, including PySpark or Scala, to process large and diverse datasets efficiently.• Examine both structured and unstructured data sources to identify trends, generate forecasts, and support data-driven decision-making.• Partner with engineers, analysts, and business stakeholders to define objectives and translate them into practical data science solutions.• Use Lakehouse principles in Databricks to manage data ingestion, transformation, storage, and model deployment in a streamlined manner.• Apply disciplined machine learning practices across feature creation, model training, testing, deployment, and ongoing performance monitoring.• Produce dashboards, visual summaries, and reports that present analytical results clearly for technical and non-technical audiences.• Maintain strong standards for data accuracy, governance, security, and compliance throughout analytics and machine learning workflows.• Improve the performance, scalability, and cost effectiveness of Databricks processing and model execution environments.
2026-08-18T00:00:00Z