Analytics Engineer (Data engineer)

The two candidates scheduled for interviews did not work out, so I will begin shortlisting the next options. If you have additional candidates in the pipeline, please send them across for consideration.Our plan is to submit the top three candidates by COB US business hours on Monday and fill the positions by Wednesday.

A candidate hired by the client last week was subsequently terminated after it was discovered that they were engaged in dual employment. As a result, the client has an immediate need to backfill the position and is prepared to prioritize interviews and finalize a candidate this week.


This is an Analytics Engineer / Data Product Engineering/Data Engineer role, NOT a Power BI Developer, Tableau Developer, Dashboard Developer, or Reporting Analyst position.

We are looking for candidates with hands-on experience building and owning data products within modern lakehouse environments using Databricks, Microsoft Fabric, Snowflake, or similar platforms.

Candidates should demonstrate Medallion Architecture (Bronze/Silver/Gold), semantic layer design, curated business-ready datasets, data governance, lineage, metadata management, and strong SQL/data transformation skills. Experience translating business concepts into governed analytical assets and working within enterprise data governance frameworks is highly preferred.

Client: McKesson
Role: Analytics Engineer (Data engineer)
Rate: C$18-30 per hour. (Canadian Dollar) – CLIENT PREFERS CANDIDATE AT LOWER RATES

• Please note that billing will be in Canadian Dollars (CAD), and candidate payments will need to be processed in Indian Rupees (INR) after applying the applicable currency conversion.

Duration: 6 months (potential extension depending on performance and results)
Interview Process: 2 Rounds of Interview
Work Model: Remote (India)
Work Hours: Please inform candidates that this role follows an 8:00 AM–5:00 PM Eastern Time schedule, which translates to approximately 6:30 PM–3:30 AM IST (Mar–Nov) and 7:30 PM–4:30 AM IST (Nov–Mar).

Reject Profiles Focused On:

• Power BI Developers
• Tableau Developers
• Dashboard/Report Developers
• Reporting Analysts
• BI Developers without hands-on Data Engineering
• Traditional ETL Developers without semantic modeling or data product ownership
• Candidates lacking Databricks, Fabric, Snowflake, or modern lakehouse platform experience

Prioritize Profiles With:

• Medallion Architecture (Bronze/Silver/Gold)
• Data Product Ownership
• Semantic Layer Design & Management
• Databricks / Fabric / Snowflake
• Data Lineage & Metadata Management
• Data Governance & Domain Modeling
• Curated Analytics-Ready Datasets
• Strong SQL and Complex Transformations
• Enterprise Analytics Engineering experience

Job Description:
Analytics Engineer Requirements:

• Very strong SQL
• Experience in ETL and complex data transformations
• Strong attention to sematic modeling
• Experience in 3-tier/medallion architectures
• Understanding of warehouse modeling - 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

About the Role
This role focuses on designing, building, and maintaining business-ready data products within the Medallion Architecture, specifically the Gold and Semantic layers.
The position is responsible for transforming curated data into business-ready models, defining KPIs, business logic, and semantic structures, and delivering trusted, analytics-ready datasets and insights.

Key Responsibilities

• Build and maintain business-ready data products and semantic models that translate curated enterprise data into accessible structures for analytics and reporting.
• Design, develop, and maintain semantic layer datasets (e.g., models, views, tabular models) aligned with business logic, KPIs, and reporting standards.
• Perform data transformations, aggregations, and modeling within the Gold/Presentation layer, applying business rules while maintaining data integrity and compliance.
• Write and optimize complex SQL queries to support analytics, reporting performance, and data model efficiency.
• Collaborate with enterprise data and governance teams to refine layer datasets, ensuring alignment between technical data structures and business requirements.
• Identify and resolve data quality, performance, and model alignment issues in partnership with enterprise data and governance teams.
• Resolve complex conflicts between business definitions, KPIs, and data models while ensuring consistency with enterprise standards.
• Document data models, semantic layers, and analytics solutions, including business definitions, mappings, and technical specifications.
• Contribute to the creation, maintenance, and evolution of Data Contracts, contextual data layers, and business ontologies, including:
  • Defining and documenting data meaning, lineage, and ownership
  • Aligning datasets to business domains, entities, and standardized definitions
  • Supporting the development of a context layer that enables consistent interpretation and reuse of data products across teams
• Collaborate with cross-functional teams to deliver scalable and governed data products.
• Ensure adherence to data governance, security, and regulatory compliance through validation, documentation, and alignment with enterprise standards.

Minimum Qualifications (Knowledge, Skills & Abilities)

• Strong proficiency in SQL for data transformation, aggregation, and analysis.
• Experience with Business Intelligence tools (e.g., Power BI) and semantic modeling.
• Understanding of data modeling concepts, including star schema and dimensional modeling.
• Experience working with curated datasets in the Gold/Presentation layer and analytics-ready data products.
• Familiarity with data governance, data quality, and metadata management concepts.
• Ability to translate business requirements into data models, KPIs, and analytics solutions.
• Experience with modern cloud data platforms such as Snowflake, Azure, Databricks, or similar technologies.
• Familiarity with version control and collaborative development practices (e.g., Git, GitHub, pull/merge request workflows).
• Experience with CI/CD workflows and collaborative development methodologies.
• Exposure to performance optimization within semantic models and reporting layers.
• Strong analytical thinking, problem-solving, and stakeholder management skills.
• Excellent communication skills with both technical and business audiences.

Business Experience

• Bachelor's degree or an equivalent combination of education and experience.
• Typically requires 3–5+ years of experience in Analytics, Business Intelligence, Data Engineering, or related data-focused roles.
• Experience delivering data products, dashboards, and semantic models in a business environment.
• Proven ability to work effectively within cross-functional teams and governed enterprise data environments.
• Experience in Healthcare or other highly regulated industries is preferred.