Analytics Engineer at GoBolt

Toronto, Ontario, Canada -

Full Time

Start Date

Immediate

Expiry Date

20 May, 26

Salary

130000.0

Posted On

19 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

dbt, SQL, Python, Dimensional Modeling, Star Schema, Kimball, Inmon, BigQuery, Snowflake, Looker, Metabase, CI/CD, Git, API, Pandas, Polars

Industry

Logistics;Transportation;Supply Chain and Storage

Description

We aren’t looking for someone to just "run queries." We are looking for the Architect of Truth. As an Analytics Engineer at GoBolt, you will be the backbone of our data platform. You’ll transform our messy operational and logistics data into elegant, high-performance dimensional models using dbt, SQL, and Python. You are someone who views a data pipeline as a product and won't rest until the "Source of Truth" is scalable, tested, and bulletproof. Salary Range: 100k-130k We are actively hiring to fill this specific position immediately. Hybrid role based in Downtown Toronto What You’ll Do Analytics-as-Code (dbt): Lead the architecture and evolution of our dbt project. You will design and maintain modular, version-controlled transformations, utilizing advanced dbt features (macros, packages, and custom tests) to ensure our Star Schema is the gold standard for logistics data. Dimensional Modeling: Design and implement robust data warehouse structures (Kimball/Inmon). You’ll bridge the gap between raw backend events and the semantic layer, ensuring our data reflects the complex reality of last-mile delivery. Full-Stack Data Engineering: Own the "T" in ELT. You’ll use Python to build custom extractors for APIs and bridge gaps in our ingestion layer, ensuring data flows seamlessly into our warehouse (BigQuery/Snowflake). The Semantic Layer & BI Performance: Optimize the interface between our warehouse and BI tools (Looker/Metabase). Reliability & CI/CD: Implement and advocate for software engineering best practices within analytics. This includes managing CI/CD pipelines for data, enforcing documentation-as-code, and building automated data quality monitoring to catch anomalies before they reach the stakeholders What We Are Looking For Experience: 3 to 5 years in Analytics Engineering or Data Engineering, specifically focused on building production-grade data pipelines. The "Product" Mindset: You treat data models like software. You care about modularity, dry code, and technical debt. You don't just fix a bug; you write a test to ensure it never happens again. Technical Stack: dbt Specialist: You are a dbt power user. You understand snapshots, incremental models, and how to optimize a DAG for cost and speed. SQL Architect: Beyond "Advanced SQL"—you understand execution plans, partitioning, and how to write code that scales with billions of rows. Python Proficiency: You’re comfortable writing scripts for data manipulation (Pandas/Polars) and interacting with REST APIs to pull niche logistics data. Modeling Expert: You can debate the merits of a bridge table vs. a flattened view and know exactly how to model a complex "Order Life Cycle." Version Control: Git is your second language. You are comfortable with branching strategies, PR reviews, and collaborative development. Bonus Points for: Logistics DNA: Prior experience with supply chain data (last-mile delivery, warehouse management systems, or routing logic). Cloud Infrastructure: Hands-on experience with GCP (BigQuery) and orchestration tools like Airflow or Dagster Certifications: dbt Analytics Engineering Certification is a massive plus Why Join Us? We are innovative, goal-oriented, and are always on the search for energetic and passionate people who are eager to learn and would like to have a rare opportunity to grow within one of Canada's fastest-growing companies. We offer a workplace where respect, diversity, and inclusion are the cornerstones of our culture. Our team members are encouraged to bring their authentic selves to work, contributing to our collective mission in their unique ways. Aside from an amazing culture, we also offer competitive salaries and a comprehensive benefits package including health, dental, and vision plans for you and your family. If you are eager to make a difference and contribute to a fast paced exciting environment, we would love to hear from you. GoBolt is an equal-opportunity employer that recognizes the value and importance of a diverse workforce. GoBolt is committed to providing assistance during all phases of the employment cycle, including recruiting through to the end of the employment relationship. If you require accommodation because of injury, illness, or disability during any portion of GoBolt’s recruiting process, please let us know by contacting your recruiter's point of contact, and we will do everything we can to accommodate you. At GoBolt, we value innovation and efficiency. In line with Ontario’s Working for Workers Act, we utilize AI-powered tools to assist in the screening and initial assessment of candidates for this position. This helps us focus on your skills and reduces bias. While AI helps us get started, your journey with us is guided by real people. Every final decision is made by a member of our team who values the unique perspective you bring.

Responsibilities

The Analytics Engineer will architect and evolve the dbt project, designing modular, version-controlled transformations to maintain a high-standard Star Schema for logistics data. They will also own the transformation layer of the ELT process, using Python to build custom extractors and optimize the interface between the data warehouse and BI tools.