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Wirelessdna

Analytics Engineer

Toronto, ON, Canada

Compensation : $75-85k (Onsite Role)

Within 25 km of Vaughan · About 16.5 km from the city centre

Apply on jobs.dayforcehcm.com About employer

Applications open in a new tab.

Job details

Pay: Compensation : $75-85k (Onsite Role)
Experience: 3–5 years of experience in a data analyst, BI engineer, analytics engineer, or similar hands-on data role.
Posted: Mar 12, 2026

Original job description

Key Responsibilities :

Data Engineering & Pipeline Development

Design and maintain data pipelines using PySpark and SQL, supporting a medallion architecture (bronze → silver → gold).

Build ingestion, transformation, and validation workflows that are clean, documented, and maintainable by others.

Apply schema validation, deduplication logic, and data integrity checks as standard practice.

Use Microsoft Fabric (Lakehouses, Dataflow Gen2, Fabric Pipelines) as the primary platform.

Reporting & Analytics

Build and maintain recurring business reports - sales performance, churn analysis, revenue variance, and commission reconciliation.

Develop and publish Power BI dashboards with DirectLake or import-mode datasets, using DAX for calculated measures and KPIs.

Translate business questions from stakeholders into accurate, well-structured data outputs.

Proactively surface anomalies and data quality issues.

Process Automation

Identify manual, repetitive reporting processes and deliver automated replacements.

Use Power Query, Dataflow Gen2, and notebook-based pipelines to streamline data preparation.

Document data models, transformation logic, and report definitions to an audit-grade standard.

Collaboration & Delivery

Work closely with business stakeholders to understand reporting requirements and validate outputs.

Scope clearly, execute promptly, and communicate blockers early.

Document data models, transformation logic, and report definitions to an audit-grade standard.

Maintain organized, version-controlled artifacts in SharePoint.

Requirements:

3–5 years of experience in a data analyst, BI engineer, analytics engineer, or similar hands-on data role.

Demonstrated experience building automated data processes that replaced manual work - not just improved it.

Strong SQL: complex queries, joins, aggregations, CTEs, and transformation logic.

PySpark / Spark SQL: notebook-based data processing and transformation.

Advanced Power BI: report development, data modelling, DAX measures, and performance optimization.

Power Query (M language): custom transformations and query optimization.

Advanced Excel: pivot tables, dynamic arrays, Power Query integration.

A genuine curiosity about AI tools and where they can be applied - you follow this space, you experiment, you have opinions.

Self-directed: you identify problems without being told and you drive solutions to completion.

Preferred / Assets

Hands-on experience with Microsoft Fabric: Lakehouses, Dataflow Gen2, Fabric Pipelines, OneLake.

Experience using LLMs or ML tools in a practical data or automation context (even prototyping counts).

Familiarity with agentic AI frameworks or AI-assisted workflow design.

Python (pandas, data wrangling) as a complement to PySpark workflows.

Exposure to telecom, dealer, or commission-based business models.

Experience building or maintaining medallion (bronze/silver/gold) data architectures.

Familiarity with Dataverse / Dynamics 365 data structures.

Background working in lean IT teams where you own the full stack from raw data to report.

Success in the First 6 Months

Success in this role is measured by reliability, trust, and manual work eliminated - not just deliverables shipped.

Core recurring reports - reconciliation, variance, churn, sales performance - are automated and running reliably with minimal manual intervention.

A material, trackable reduction in time spent by the business on recurring manual data tasks.

At least one AI-assisted workflow is live and demonstrably replacing a previously manual process.

Power BI dashboards are trusted by stakeholders as the definitive source of truth for key metrics.

Data pipelines are clean, documented, and maintainable by the broader team without your involvement.

Ad hoc analysis requests are turned around quickly with accurate, well-presented outputs.

The Sr. IT Manager’s time on routine data tasks is materially reduced.

Why This Role

This is not a “maintain the status quo” hire. We have a real mandate to modernize how data is managed and delivered across the business, leadership that supports it, and the infrastructure investment already underway. If you are someone who gets energized by owning data end-to-end - from the pipeline that builds it to the dashboard that tells the story - this role was built for you.

Compensation : $75-85k (Onsite Role)

Apply on jobs.dayforcehcm.com About employer

More about this job

Responsibilities

The Analytics Engineer at Wirelessdna will build data pipelines in Microsoft Fabric, create and maintain reports and Power BI dashboards, and automate manual data work. They will also work with business stakeholders to deliver accurate, documented data outputs.

Requirements

Candidates need 3 to 5 years in a hands-on data role, strong SQL, PySpark, Power BI with DAX, Power Query and advanced Excel. They must have built automated processes that replaced manual work and be self-directed.

Skills

PySpark
Spark SQL
SQL
Power BI
DAX
Power Query
M language
Microsoft Fabric
Lakehouses
Dataflow Gen2
Fabric Pipelines
OneLake
Advanced Excel
Pivot tables
Dynamic arrays
Python
pandas
Data modelling
Data validation
Deduplication
Schema validation
Medallion architecture
Process automation
Report automation
Documentation

Keywords

Analytics Engineer
PySpark
SQL
Spark SQL
Power BI
DAX
Power Query
M language
Microsoft Fabric
Lakehouse
Dataflow Gen2
Fabric Pipelines
OneLake
Medallion architecture
Data pipelines
Business intelligence
Reporting automation
Excel
Python
pandas

Tools

Microsoft Fabric
Power BI
Power Query
Excel
SharePoint
PySpark

Languages

English

Seniority

Mid level

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