BI Data Engineer

Full stack engineer for BI / Reporting solution

Location: Markham, ON (Hybrid)

Employment Type: Full-Time

Department: Business Intelligence / Data Analytics

Reporting To: Director, BI / Analytics

Seniority Level: Intermediate (2–5 years)

Compensation & Role Details:

Expected Salary Range: The expected base salary range for this role is between $100,000 – $115,000 CAD, depending on experience and qualifications

Role Type: New Role

AI Disclosure: AI may be used during the hiring process.

Role Overview

We are seeking a BI Data Engineer to design, build, and optimize BI assets — dashboards, reports, and semantic data models — primarily in AWS QuickSight on top of SQL-based datasets. This is a hands-on BI role that involves building data models, data pipelines and a web presentation layer. Your day is spent turning business ask into governed, performing dashboards and reports served through web application and build / maintain SQL models behind them.

Key Responsibilities

BI Solution Development

• Build interactive QuickSight dashboards (parameters, controls, calculated fields).
• Implement data visualizations that clearly communicate business insights.
• Apply security and data-governance standards across BI assets.

Data Analysis & Modeling

• Write and optimize complex SQL for extraction, transformation, aggregation and performance tuning.
• Design semantic layers and curated datasets aligned to reporting needs.
• Monitor and troubleshoot BI solutions for accuracy, performance, scale and efficiency.

Data Pipeline Engineering

• Contribute to data acquisition, wrangling, shaping and validate data quality and lineage for reporting.
• Orchestrate and manage data shaping jobs that run in Cloud to maintain a high quality data model

Web Application Upkeep & Maintenance

• Application layer built with OAuth, Node.JS, Express.JS, MongoDB, SQL and .NET

Must-Have Qualifications

• 2–5 years in a BI / reporting development role.
• Strong SQL: complex joins, window functions, CTEs, aggregations, and query performance tuning.
• Strong data wrangling, pipeline and basic web development skills. Experience with .NET, Java Script, Python and CSS.
• Good understanding of data warehousing and dimensional modeling (star schemas, semantic layers).
• Good AWS QuickSight experience. Knowledge of parameters, controls, calculated fields and dataset design.
• Hands on AWS Cloud experience. Knowledge of AWS data services: S3, Lambda and IAM basics.
• Hands on experience with Git and typical development workflows.
• Comfortable with work needed to improve data quality & produce reports users can rely on
• Good communication skills.

Nice-to-Have Skills

• Maintaining web application, fixing defects and testing fixes
• Experience with Google charts API
• Building and maintaining API layer for data acquisition and data services
• Automating data jobs that can run at scale
• Experience delivering email digests, Narrative summaries that go beyond classic reports, dashboards, analytics
• Knowledge of SPICE and row-level security
• Experience using AI tools to accelerate development
• Experience with Mongo DB
• Experience with Docker and container deployments
• Experience with Service Bus
• Experience with pandas Data Frames
• End to end experience going from data acquisition through presentation layer in a production setting
• Data governance exposure (cataloging, lineage, definitions)
• Continuous integration / Continuous Delivery (CI/CD) for BI assets.
• Knowledge of BI solutions like Power BI, Looker
• Knowledge of Data lake / Data warehouse solutions like Snowflake, DataBricks
• Experience automating QA
• Experience with build tools like Jenkins
• Experience with Cloud Ops, Dev Ops and automation
• Experience building prediction models
• Building interactive chat type solutions over existing data assets
• Best Visualization practices and UX for analytics

Key Competencies

• Data Storytelling: Translates complex data into clear visuals and narratives.
• Fast Learner: Curious and fast paced learner that can adapt to change;
• Bias for Action: Ships iteratively, validate quickly and improve continuously.
• Quality & Accuracy: High attention to detail; strong testing discipline. Security consciousness
• Customer Focus: Collaborates with business partners to understand and deliver high-value insights.
• Ownership & Scope Discipline: Proactive in monitoring and support; comfortable owning BI/reporting deliverables