RQ-2026-009815 - Senior Business Intelligence Specialist for Virtual Products Development

Project Overview

The Agency is expanding the Provincial Health Services Directory (PHSD) analytics platform to provide comprehensive operational, clinical, and business intelligence reporting supporting provincial healthcare programs and internal stakeholders. The project will develop an enterprise analytics platform that consolidates operational and healthcare data from multiple provincial systems, including PHSD, Smile CDR, AWS HealthLake, Provider Registry, Master Data Management, identity management platforms, video collaboration platforms, and other digital health assets. The platform will support executive reporting, operational dashboards, healthcare analytics, adoption metrics, provider activity reporting, referral analytics, and service utilization reporting. The solution includes designing scalable data ingestion pipelines, developing ETL processes using AWS Glue and Python, implementing dimensional data models within Amazon Redshift, and developing interactive Power BI dashboards enhanced with AI-assisted analytics, natural language insights, forecasting, and advanced visualization capabilities. The platform will provide timely, accurate, and actionable insights for healthcare providers, operational teams, executives, and provincial stakeholders while supporting secure, governed, and scalable analytics.

Key Responsibilities

• Design, develop, and maintain enterprise Power BI dashboards supporting operational, executive, clinical, and business reporting.
• Develop AI-assisted dashboards utilizing Power BI Copilot, natural language queries, AI visualizations, forecasting, anomaly detection, and intelligent insights where appropriate.
• Design and implement enterprise data warehouse solutions using Amazon Redshift.
• Develop dimensional star schemas, fact tables, dimension tables, and semantic models supporting enterprise reporting.
• Develop AWS Glue ETL pipelines using Python to ingest, transform, validate, and load data into Amazon Redshift.
• Develop automated data ingestion processes from NetIQ IAM, Pexip, Zoom, Smile CDR, AWS HealthLake, Provider Registry, Master Data Management, PHSD operational databases, application logs, and other provincial digital health assets.
• Develop data quality validation, cleansing, reconciliation, and governance processes supporting analytics accuracy.
• Optimize Redshift performance, partitioning, indexing strategies, query execution, and warehouse scalability.
• Develop operational KPIs, healthcare utilization metrics, provider activity reports, referral analytics, platform adoption reporting, and executive dashboards.
• Collaborate with business stakeholders to gather reporting requirements and develop meaningful analytics solutions.
• Develop deployment pipelines and knowledge transfer materials.
• Support production implementation, troubleshooting, report optimization, and ongoing analytics enhancements.
• Create documentation for data models, ETL processes, report definitions, data lineage, metadata, and operational procedures.
• Develop automated deployment pipelines, testing procedures, and operational transition documentation.

Qualifications & Requirements

REQUIRED

• Must be able to work onsite
• Senior experience designing and developing enterprise Business Intelligence and analytics solutions.
• Extensive experience developing Power BI dashboards, reports, semantic models, and datasets.
• Experience developing dimensional data warehouses using star and snowflake schemas.
• Experience developing ETL and ELT processes using Python and AWS Glue.
• Advanced SQL development for Amazon Redshift and relational databases, including query optimization and performance tuning.
• Data integration from REST APIs, FHIR APIs, Smile CDR, AWS HealthLake, NetIQ IAM, Pexip, Zoom, Provider Registry, Master Data Management, and enterprise databases.
• AWS analytics services including Amazon Redshift, AWS Glue, S3, Athena, IAM, CloudWatch, and related cloud services.
• Healthcare analytics using FHIR R4/R4B, HL7 v2, SMART on FHIR, and healthcare interoperability standards.
• Experience implementing secure data access using IAM, OAuth2/OIDC, and role-based security.
• Experience evaluating AI accuracy, hallucination reduction, grounding, and response quality.
• Experience with Pexip and Zoom APIs and data structures.
• Experience with NetIQ IAM APIs and data structures.
• Experience with AWS Bedrock.
• AI-assisted analytics including Power BI AI capabilities, natural language insights, forecasting, anomaly detection, and intelligent reporting.
• Data quality management, governance, reconciliation, validation, and operational reporting.
• Strong analytical, communication, documentation, stakeholder engagement, and knowledge transfer skills.
• Public sector experience.

NICE TO HAVE

• Python Glue shell experience
• Experience with Pexip and Zoom APIs, extracting data for analytics

EVALUATION CRITERIA

• Business intelligence, dashboard development, Power BI reporting, semantic models, executive reporting, KPI development, and AI-assisted analytics experience - 25 points
• Enterprise data engineering experience including Amazon Redshift, AWS Glue, Python, SQL, dimensional modelling, ETL/ELT development, and enterprise data warehouse design - 25 points
• Healthcare analytics and interoperability experience including Smile CDR, AWS HealthLake, FHIR R4/R4B, HL7 v2, NetIQ IAM, Pexip, Zoom, healthcare APIs, and enterprise healthcare data integration - 25 points
• Experience working with digital health assets including PHSD, Hospital Report Manager (HRM), Enterprise Master Data Management, stakeholder engagement, documentation, and knowledge transfer - 25 points

Key Skills & Competencies

Power BI, SQL, Amazon Redshift, AWS Glue, Python, ETL, ELT, Dimensional modelling, Star schemas, Snowflake schemas, Data warehousing, REST APIs, FHIR, HL7 v2, Smile CDR, AWS HealthLake, IAM, OAuth2, OIDC, Pexip, Zoom, NetIQ IAM, AWS Bedrock, S3, Athena, CloudWatch, Healthcare analytics, SMART on FHIR, AI analytics, Natural language queries, Forecasting, Anomaly detection, Data quality, Governance, Reconciliation, Validation, Query optimization, Performance tuning, Business intelligence, Enterprise reporting, Semantic models, Data integration, Data pipelines, Data ingestion, KPIs, Performance optimization, Data modelling