About this role
Job Description
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.
- Strong 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.<