Design and implement cloud-based data lake/lakehouse structures and automated ETL pipelines on Azure. Develop analytics and ML/NLP models, create dashboards, prioritize AI use cases, and transfer knowledge to PHO staff to sustain the platform and HealthMap ingestion.
The role combines two functions. As a Data Engineer, it
automates the data pipeline for analytic products and advanced analyses. As a
Data Science Specialist, it helps identify and prioritize use cases and
integrate AI techniques (machine learning, NLP) into PHO’s work, increasing
capacity for modelling, forecasting, and scenario analysis. The role supports
both foundational capability/infrastructure work and HealthMap data ingestion
and aligns with and advances the Public Health Data Utility (PHDU) on PHO’s
Azure platform.
Key Responsibilities
- Participate in product teams to analyze system requirements,
and architect, design, code, and implement cloud-based data and analytics
products that conform to standards.
- Design, create, and maintain cloud-based data lake and
Lakehouse structures, automated data pipelines, analytics models, and
visualizations (dashboards and reports).
- Liaise with IT colleagues to implement products, conduct
reviews, resolve operational problems, and support business partners in the
effective use of cloud-based data and analytics products.
- Analyze complex technical issues, identify alternatives, and
recommend solutions.
- Prepare and conduct knowledge transfer.
- Automate the data pipeline for analytic products and
advanced analyses, including ingestion, ETL, and production for the
foundational capability and for HealthMap (DLSPH model data).
- Help identify and prioritize analytic use cases and
integrate AI techniques (machine learning, NLP) into PHO’s work.
- Increase PHO’s capacity for modelling, forecasting, and
scenario analysis.
- Build on and advance the PHDU and PHO’s Azure data and
analytics platform; support data acquisition through data-sharing and
governance processes where required.
- Document methods and transfer knowledge to PHO staff so the
pipeline and capability can be sustained beyond the engagement.
Key Deliverables
- Automated data pipelines and cloud data lake / Lakehouse
structures supporting the capability and HealthMap.
- Analytics models and visualizations (dashboards and reports)
conforming to standards.
- Prioritized AI / ML use cases and supporting models
(forecasting, scenario analysis).
- Knowledge-transfer documentation and sessions for PHO
technical staff.
Requirements
Required Skills
- Experience with multiple cloud-based data and analytics
platforms and coding / programming / scripting tools to create, maintain,
support, and operate cloud-based data and analytics products.
- Experience designing, creating, and maintaining cloud-based
data lake and Lakehouse structures, automated data pipelines, analytics models,
medallion architecture, and visualizations (dashboards and reporting) in
real-world implementations.
- Deep experience with modern technology stacks: Azure
Storage, Azure Data Lake, Azure Databricks Lakehouse, and Azure Synapse. Power
BI, Python, SQL, Azure Databricks, and Azure Data Factory.
- Experience assessing client information-technology needs and
objectives.
- Experience problem-solving to resolve complex,
multi-component failures.
- Experience preparing knowledge-transfer documentation and
conducting knowledge transfer.
- A team player with a track record for meeting deadlines.
Desirable Skills
- Written and oral communication skills to participate in team
meetings, write and edit systems documentation, prepare and present written
reports on findings and alternative solutions, and develop guidelines / best
practices.
- Interpersonal skills to explain and discuss the advantages
and disadvantages of various approaches.
- Experience conducting knowledge-transfer sessions and
building documentation for technical staff on architecting, designing, and
implementing end-to-end data and analytics products.
Expected Skills
- Be an advanced professional able to apply concepts,
practices, and procedures in practice.
- Work with minimal direction and lead and train others in
technical components and concepts.
- Plan, lead, and deliver complex deliverables that provide
options for decisions within the organization.
- Bring a high level of expertise in the required skill set,
specialized in the technical area, and provide specific advisory support as
required.
Must Haves:
- Experience with multiple cloud-based data and analytics
platforms and coding / programming / scripting tools to create, maintain,
support, and operate cloud-based data and analytics products.
- Experience designing, creating, and maintaining cloud-based
data lake and Lakehouse structures, automated data pipelines, analytics models,
medallion architecture, and visualizations (dashboards and reporting) in
real-world implementations.
- Deep experience with modern technology stacks: Azure
Storage, Azure Data Lake, Azure Databricks Lakehouse, and Azure Synapse. Power
BI, Python, SQL, Azure Databricks, and Azure Data Factory.
- Experience assessing client information-technology needs and
objectives.
- Experience problem-solving to resolve complex,
multi-component failures.
- NOTE: We are looking for the same candidate to
cover both data engineering/data pipeline work and data science specialist
work.
Similar Jobs
eCommerce • Fashion • Retail • Sales • Wearables • Design
Lead regional retail training and customer experience initiatives, deliver and implement sales, service, and clienteling programs, monitor KPIs, coach store teams and managers, support onboarding and digital tool adoption (Coach Journey, Client Compass), and drive consistent brand service standards across the market.
Top Skills:
Client CompassCoach JourneyExcelMS OfficePowerPointWord
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Build and operate ingestion, reconciliation, and reporting systems that reconcile card-network and partner settlement files against internal transactions. Deliver end-to-end features for traceability, accounting journals, tax and regulatory reporting, and compliance tooling while ensuring reliability, scalability, and data privacy.
Top Skills:
Ai ToolsAirflowAWSBigQueryCi/CdDelta LakeGoHadoopIso-8583JavaKafkaKubernetesObservabilityPysparkPythonSnowflakeSparkSQLTemporalTerraform
Blockchain • eCommerce • Fintech • Payments • Software • Financial Services • Cryptocurrency
Lead development and implementation of AI legal and compliance frameworks. Conduct cross-functional AI reviews, maintain governance docs (model cards, impact assessments), partner with engineering on transparency and fairness requirements, build incident response and monitoring processes, and scale AI legal review workflows.
Top Skills:
Ai/MlAlgorithmic Impact AssessmentGenerative AiLlmsModel CardsModel Monitoring
What you need to know about the Toronto Tech Scene
Although home to some of the biggest names in tech, including Google, Microsoft and Amazon, Toronto has established itself as one of the largest startup ecosystems in the world. And with over 2,000 startups — more than 30 percent of the country's total startups — Toronto continues to attract new businesses. Be it helping entrepreneurs manage their finances, simplifying business operations by automating payroll or assisting pharmaceutical companies in launching new drugs, the city's tech scene is just getting started.


