Hybrid Senior Data Engineer: Fabric & BI Platform Lead

cmls

Vancouver

On-site

CAD 90,000 - 130,000

Full time

10 days ago

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Benefits offered by this job

Competitive compensation

Health coverage

4 weeks vacation

RRSP matching

Learning & growth

Job summary

Nesto Group in Canada is seeking a data engineer to own the Commercial Analytics data platform in Microsoft Fabric, guiding data ingestion, modeling, security and serving across Power BI reports and internal tools.

You will lead initiatives from requirements through production, migrate pipelines, and expand CI validation alongside our DevOps processes. Strong SQL, Python and REST API skills are essential in a collaborative, growth-oriented environment.

Qualifications

3+ years of data engineering experience.
Hands-on Microsoft Fabric experience preferred; Azure Data Factory/Synapse or Databricks experience also valuable.
Advanced SQL on large relational datasets; performance tuning and incremental loads.
Strong dimensional modeling experience using Kimball methodology.
Experience building datasets for Power BI; familiarity with DAX and Power Query.
Python (PySpark or pandas) for ingestion, validation, and automation.
Experience integrating REST APIs with authentication, pagination and rate limits.
Governance practices: access control, data security and usage monitoring.
Git-based development and CI/CD, ideally with Azure DevOps.
Daily use of AI coding tools; Claude Code preferred.
Experience leading data projects end-to-end; strong communication with stakeholders.

Responsibilities

Lead data initiatives end-to-end: gather requirements from stakeholders and deliver production-ready solutions.
Decide on ingestion, transformation, storage and modeling architecture across lakehouses, warehouses and environments.
Design and maintain ELT pipelines from SQL Server, Azure SQL, REST APIs and SaaS platforms with incremental loads and safe reruns.
Develop dimensional data models for analytics and reporting.
Build views, stored procedures and curated tables behind Power BI semantic models and dashboards.
Implement data validation, monitoring, logging and alerting to resolve issues quickly.
Tune queries and pipelines for performance as data volumes grow.
Manage access control, provisioning and data sharing with internal teams and partners.
Document lineage, architecture and data processes; review code and set engineering standards.
Evaluate Fabric features, run PoCs and drive improvements.