4 results for Database Manager in Toronto, ON

Database Developer

Mississauga, ON
onsite
Contract / Temporary
45 - 65 CAD / Hourly
We are looking for an experienced Database Developer to join a non-profit organization in Mississauga, Ontario on a Long-term Contract basis. This position will play a key role in strengthening reporting capabilities by building reliable data solutions and translating business needs into effective Power BI outputs. The successful candidate will bring strong technical expertise in Microsoft SQL Server and modern reporting tools, along with the ability to work with finance-related datasets in a structured and accurate manner. Responsibilities: • Transform existing reporting assets into Power BI solutions, including redesigning selected reports and developing new dashboards where needed. • Review current database queries, scripts, and reporting logic to identify opportunities for improved performance, accuracy, and maintainability. • Build and refine Power BI data models to support clear, meaningful, and scalable reporting for business stakeholders. • Use Power Query and related development techniques to prepare, shape, and connect data from multiple sources for analysis. • Develop, test, and optimize SQL components such as stored procedures, complex queries, and database objects to support reporting needs. • Partner with internal teams to deliver approximately 10 to 15 finance-focused reports with a high standard of quality and consistency. • Contribute to reporting project planning by helping track priorities, timelines, and deliverables throughout the engagement. • Support broader data and reporting initiatives by applying best practices in performance tuning, indexing, and data warehousing.
2026-06-29T00:00:00Z

Data Engineer

Toronto, ON
onsite
Permanent
100000 - 120000 CAD / Yearly
Robert Half is working with a global, consumer‑facing organization that’s scaling its data platform to better support marketing, sales, and customer analytics. They’ve recently invested heavily in their data stack and are growing their Data Engineering team to meet rising demand from the business.This is an intermediate‑level role where you’ll work closely with marketing stakeholders, BI, and software engineering to deliver trusted, analytics‑ready data. What you’ll be doing<ul><li>Partner directly with Marketing and Sales teams to understand data requirements</li><li>Design and build data models that power dashboards and analysis</li><li>Build and maintain data pipelines end‑to‑end</li><li>Work with cloud data platforms to ensure performance and reliability</li><li>Collaborate closely with BI and software engineering teams</li></ul>Tech environment<ul><li>Cloud data warehouse (AWS‑based, Redshift‑style)</li><li>SQL & Python</li><li>dbt for data modelling</li><li>Fivetran (or similar) for ingestion</li><li>Airflow for orchestration</li><li>BI tooling (Looker‑type stack)</li><li>Strong Salesforce / marketing data footprint</li><li>(Marketing Cloud / CRM / customer data experience is highly relevant)</li></ul>
2026-06-25T00:00:00Z

Data Analyst

Markham, ON
onsite
Contract / Temporary
23.75 - 27.5 CAD / Hourly
We are looking for a Data Analyst to join a utilities and infrastructure organization in Markham, Ontario on a Long-term Contract basis. In this role, you will turn complex product and customer data into practical insights that support the growth and performance of a water-focused portfolio. You will work with partners across the business to strengthen reporting, guide planning decisions, and improve outcomes across the product lifecycle. Responsibilities: • Examine product, customer, and revenue data to identify trends in acquisition, retention, pricing performance, and overall profitability. • Build and maintain dashboards and reporting tools that give stakeholders clear visibility into portfolio performance and emerging opportunities. • Perform market and customer analysis to support product planning, prioritization, and longer-term strategic direction. • Provide analytical support for product lifecycle activities, including tracking portfolio changes, measuring unit growth, and assessing attrition patterns. • Support the launch of new offerings by preparing forecasts, monitoring early results, and highlighting areas that require adjustment. • Work with product leadership to assess pricing approaches, review promotional results, and recommend improvements based on data. • Contribute to business cases for new initiatives by gathering insights, validating assumptions, and quantifying potential impact. • Partner with Finance, Supply Chain, Sales, Marketing, Engineering, and Field Operations to support forecasting, margin analysis, go-to-market readiness, and cross-functional execution.
2026-06-22T00:00:00Z

Data Scientist

North York, ON
onsite
Permanent
100000 - 120000 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.
2026-06-07T00:00:00Z