Analytics Engineer

Client McKesson(Apex) Company: Compunnel Technology Role: Analytics Engineer Mode of work: Remote Experience: 0.6 to 1 year Shift Timings : ( 8 am - 5 pm EST OR 5:30 pm IST – 2:30 am IST ) Employment Type: Contractual 6 months About the role: This role sits within the McKesson Canada Specialty Health team and focuses on designing, building, and maintaining business-ready data products in the Medallion Architecture, Gold, and Semantic layers. This position will focus on transforming curated data into business-ready models, defining KPIs, business logic, and semantic structures, and delivering trusted, analytics-ready datasets and insights Overview: Manager seeking 1 Analytics Engineer to support his FTE in building the scorecard. Typical workflow: Strategic Insights is an internal/external facing team responsible for gathering requirements and passing them over to Gabor's team, which is responsible for the deliverables (building the reports themselves). Depending on complexity, they may also be passed to the internal IT Team. The build of the Scorecard outlined above will land on Gabor's team, with internal IT supporting the data engineering efforts. The Analytics Engineer is not a traditional data engineering role - they will work as a conduit between the FTE building the dashboard and IT's Data Hub Team to understand and analyze the data requirements, performing the data mappings, determining the transformations needed, and detailing to the data engineers what needs to be built. They will need to "roll up their sleeves" and support builds, if necessary. Tech skills needed: SQL, ETL, data transformations from multiple sources, normalization, strong attention to semantic modelling and working within 3-tier/medallion architectures. Existing data infra state: they are on a transformation journey and launched a new CRM 2 months ago. For the scorecard, data sources will span both the old and new (will need to combine, understanding that there will be different fields, names, etc.), adding one layer of complexity. Their customer-facing application requires a common data platform but only includes that single application (60-70% of patient support data). Their team is responsible for filling 30% of the data, but that's only 1 data model. Retention and other core KPIs for the scorecard is a "house of cards" when it comes to the data sources. Adding additional layers of complexity. At a high level, they are working across 2 core deliverables for the year: the first being the scorecard (fed by these systems) and the second being migrating this data over to their Snowflake platform and build out data models for pharmacy and other operations. While Gabor's team is not responsible for the migration to Snowflake, they cannot decouple the scorecard build from the move given the data dependencies. Analytics Engineer Requirements: Very strong SQL Experience in ETL and complex data transformations Strong attention to semantic modelling Experience in 3-tier/medallion architectures Understanding of warehouse modelling - fact and dimensions, star/snowflake schemas Experience in BI tooling (understanding the data requirements for BI development and how data is sourced for BI) Experience in Snowflake, Databricks, or similar cloud-native data warehouse. Education: Bachelors Degree