HM Note: This hybrid contract role is three (3) days in office. Candidate resumes must include first and last name, email and telephone contact information.

Description

- The Agency requires a Senior Business Intelligence Specialist with strong Oracle experience to support the Ontario Clinical Report Exchange (OCRE) project. The resource will develop the data integration and reporting capabilities needed to extract information from Oracle and OCRE application sources, load it into Amazon Redshift, and make reliable operational and business information available to OCRE stakeholders. The role will build AWS Glue Python Shell jobs and supporting SQL to extract, transform, validate, and load data into Amazon Redshift, while using AWS Database Migration Service (AWS DMS) where replication or change-data-capture capabilities are required.

In Redshift, the resource will design a star-schema reporting layer with fact and dimension structures, views, or materialized views appropriate to the reporting workload. The resource will then develop Power BI semantic models, reports, and dashboards for operational metrics, data-quality monitoring, and other reporting needs defined by OCRE business stakeholders. The work requires an understanding of the Ontario HRM Standard, FHIR data structures, and HL7 v2 data structures so that clinical and operational data is interpreted and modelled correctly.

Required Experience:

- Senior-level Oracle experience, including complex SQL, PL/SQL, data extraction, performance tuning, data profiling, and analysis of production data structures.
- Hands-on experience developing AWS Glue Python Shell jobs and Python-based ETL processes that extract, transform, validate, and load data into Amazon Redshift.
- Strong experience with Amazon Redshift, AWS DMS, dimensional modelling, star schemas, incremental data loads, reconciliation, and data-quality controls.
- Robust Power BI experience, including semantic models, DAX measures, Power Query, report design, dashboard development, refresh processes, and performance optimization.
- Practical experience interpreting the Ontario HRM Standard, FHIR data structures, and HL7 v2 data structures for healthcare reporting and analytics.

Responsibilities:

- Work with OCRE business and technical stakeholders to define reporting requirements, business measures, data-quality indicators, acceptance criteria, and dashboard priorities.
- Analyze Oracle schemas and OCRE application data sources to identify authoritative fields, relationships, business rules, data limitations, and extraction requirements.
- Develop, test, and support AWS Glue Python Shell jobs that extract data from Oracle and OCRE application sources and load it into Amazon Redshift.
- Configure or support AWS DMS replication and change-data-capture processes where they are used to move Oracle or application data into the reporting platform.
- Implement full and incremental load patterns, transformations, validation rules, error handling, logging, reconciliation, restartability, and operational monitoring for data pipelines.
- Design and maintain the Amazon Redshift reporting model, including staging structures, fact and dimension structures, keys, history handling, and star-schema relationships.
- Create and optimize Redshift SQL views, materialized views, stored procedures, and queries that expose governed reporting datasets to Power BI.
- Develop Power BI semantic models, DAX measures, Power Query transformations, reports, and dashboards for OCRE metrics, operational performance, and data quality.
- Translate Ontario HRM, FHIR, and HL7 v2 data elements into consistent analytical definitions while preserving clinical meaning, traceability, and source-system context.




- Profile source and target data, identify anomalies or gaps, implement data-quality rules, and reconcile dashboard results to Oracle and OCRE source data.
- Tune Oracle queries, AWS Glue jobs, Redshift workloads, and Power BI models to meet agreed performance, refresh, scalability, and support requirements.
- Prepare technical designs, source-to-target mappings, dimensional models, metric definitions, test evidence, deployment instructions, runbooks, and knowledge-transfer materials.

Desired Skills:

- Experience designing dimensional models using fact tables, dimension tables, conformed dimensions, surrogate keys, slowly changing dimensions, and auditable metric definitions.
- Experience with Redshift performance features such as distribution styles, sort keys, workload management, query plans, materialized views, and columnar data design.
- Experience with Power BI row-level security, deployment pipelines, scheduled refresh, gateways, workspace governance, usage monitoring, and accessibility practices.
- Experience supporting healthcare analytics solutions that require data lineage, privacy-aware access, auditability, reconciliation, production monitoring, and incident investigation.

Required Skills:

- Oracle, Python, AWS Glue Python Shell, and AWS DMS experience, including complex SQL, source-data analysis, extraction, transformation, incremental loading, validation, reconciliation, and production support.
- Amazon Redshift and dimensional-modelling experience, including staging layers, fact and dimension structures, star schemas, views or materialized views, SQL optimization, and reporting-layer performance tuning.
- Power BI development experience, including semantic modelling, DAX, Power Query, dashboards, operational metrics, data-quality reporting, refresh processes, security, and performance optimization.
- Healthcare-data experience involving the Ontario HRM Standard, FHIR data structures, and HL7 v2 data structures, including mapping source data to consistent analytical definitions and metrics.

Rated Criteria:

1. Oracle, Python, AWS Glue Python Shell, and AWS DMS experience, including source analysis, complex SQL, ETL development, incremental loading, validation, reconciliation, and production support. 25 points
2. Amazon Redshift and dimensional-modelling experience, including staging structures, fact and dimension models, star schemas, views or materialized views, SQL optimization, and workload performance. 25 points
3. Power BI experience, including semantic models, DAX, Power Query, dashboards, operational metrics, data-quality reporting, refresh, security, and performance optimization. 25 points
4. Ontario HRM Standard, FHIR, and HL7 v2 data-structure experience, including healthcare-data mapping, metric definition, traceability, and interpretation of clinical and operational data. 25 points

Total: 100 Points

Deliverables

- Production-ready AWS Glue Python Shell jobs and supporting Python or SQL components that extract data from Oracle and OCRE application sources and load it into Amazon Redshift.
- AWS DMS configurations, mappings, validation results, and operational documentation for replication or change-data-capture workflows assigned to the resource.
- Amazon Redshift staging, ingestion, transformation,



and reconciliation components supporting full and incremental data loads.
- A governed Redshift star-schema reporting layer containing the required fact and dimension structures, relationships, history handling, and business definitions.
- Optimized Redshift views, materialized views, stored procedures, and queries that provide Power BI with reliable and supportable reporting datasets.
- Power BI semantic models, DAX measures, Power Query transformations, reports, and dashboards for OCRE metrics, operational monitoring, data quality, and stakeholder-defined reporting needs.
- Documented metric definitions, source-to-target mappings, data-quality rules, validation controls, lineage, and reconciliation results.
- Automated and manual test assets covering extraction, transformation, incremental loads, data completeness, data accuracy, report calculations, refresh, regression, and release validation.
- Operational logging, monitoring, alerting, restart, recovery, incident-investigation, and support procedures for the data pipelines and reporting solution.
- Technical designs, dimensional models, configuration notes, deployment instructions, runbooks, demonstrations, defect fixes, release support, and knowledge-transfer materials.

Knowledge Transfer Details:

- The resource will provide ongoing knowledge transfer to the Ontario Health OCRE team throughout the engagement.
- The resource will document Java/Spring Boot services, HAPI FHIR processing, NextGen Connect channels, HL7 v2 and FHIR mappings, Ontario HRM Standard implementation details, Pub/Sub integration, ReactJS components, security configuration, and Docker deployment procedures.
- The resource will participate in code reviews, design walkthroughs, interface and data-mapping reviews, demonstrations, release reviews, operational-readiness reviews, and technical handover sessions.
- All key source code, configuration, tests, technical documentation, runbooks, and lessons learned will be shared with Ontario Health leads before the end of the engagement.
- The resource will support transition planning so Ontario Health staff and successor resources can operate, maintain, troubleshoot, and enhance the delivered OCRE components.
- The resource will ensure full knowledge transfer is provided to the Agency team before end of engagement. Some of this might occur at the end of the engagement but will also be shared as information is obtained/consolidated. Key deliverables will be shared with team.
- The resource must provide all related documentation as part of knowledge transfer protocol. Documents will be reviewed by the appropriate leads and signed off by manager/director.
- The resource will work collaboratively with the Agency team throughout the assignment and ensure key deliverables, milestones, and documentation are shared.
- A walkthrough of any demos, development, etc. will be required before the end of the engagement.

Must Haves:

- Oracle, Python, AWS Glue Python Shell, and AWS DMS experience, including complex SQL, source-data analysis, extraction, transformation, incremental loading, validation, reconciliation, and production support.
- Amazon Redshift and dimensional-modelling experience, including staging layers, fact and dimension structures, star schemas, views or materialized views, SQL optimization, and reporting-layer performance tuning.
- Power BI development experience, including semantic modelling, DAX, Power Query, dashboards, operational metrics, data-quality reporting, refresh processes, security, and performance optimization.
- Healthcare-data experience involving the Ontario HRM Standard, FHIR data structures, and HL7 v2 data structures, including mapping source data to consistent analytical definitions and metrics.

📌 Business Intelligence Specialist Oracle (Toronto)
🏢 Foilcon
📍 Toronto