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Data Scientist - Data Analytics and Infrastructure

Toronto, ON, Canada

Pay
Salary not listed in the saved posting
Work setup
Unconfirmed
Employment
Unconfirmed
Apply at Ample Insight Inc.

What you’ll bring

All qualifications

Core experience

  • Experience building and maintaining data pipelines and infrastructure in production environments
  • Proficient in SQL and data wrangling at scale (e.g., Spark, Airflow, dbt, etc.)
  • Familiarity with cloud data platforms (e.g., AWS, GCP, Azure)
  • Ability to design data schemas and implement analytics tracking strategies
Qualification wording
Experience building and maintaining data pipelines and infrastructure in production environments
Proficient in SQL and data wrangling at scale (e.g., Spark, Airflow, dbt, etc.)
Familiarity with cloud data platforms (e.g., AWS, GCP, Azure)
Ability to design data schemas and implement analytics tracking strategies
Education & alternatives
Qualifications - BS (or higher, e.g., MS, or PhD) in Computer Science, Data Engineering, or a related technical field - Experience building and maintaining data pipelines and infrastructure in production environments

Tools in this posting

  • Python
  • SQL
  • AWS
  • dbt
  • Google Cloud (GCP)
  • Spark
  • Tableau
  • Airflow
  • NumPy
  • pandas
  • Azure
  • Power BI
Source — Tool mentions in context
- Strong grasp of statistics, data modeling, and performance tuning - Skilled in Python (Pandas, Numpy, etc.) and data visualization tools (e.g., Tableau, Power BI) - Familiarity with cloud data platforms (e.g., AWS, GCP, Azure)
- Experience building and maintaining data pipelines and infrastructure in production environments - Proficient in SQL and data wrangling at scale (e.g., Spark, Airflow, dbt, etc.) - Strong grasp of statistics, data modeling, and performance tuning
- Skilled in Python (Pandas, Numpy, etc.) and data visualization tools (e.g., Tableau, Power BI) - Familiarity with cloud data platforms (e.g., AWS, GCP, Azure) - Ability to design data schemas and implement analytics tracking strategies

Job description

View original posting ↗

Job Description

We are looking for Data Scientists passionate about Data Analytics and Infrastructure, with strong foundations in data engineering, analytics, and statistics. You should enjoy working with large, complex datasets and developing efficient pipelines that enable scalable, reliable data analytics.

You’ll be responsible for designing and maintaining data infrastructure, automating workflows, and enabling data accessibility across teams. Your work will directly impact business decisions by delivering high-quality insights and building robust analytics systems. Strong problem-solving, communication, and collaboration skills are key for this role.

Qualifications

  • BS (or higher, e.g., MS, or PhD) in Computer Science, Data Engineering, or a related technical field

  • Experience building and maintaining data pipelines and infrastructure in production environments

  • Proficient in SQL and data wrangling at scale (e.g., Spark, Airflow, dbt, etc.)

  • Strong grasp of statistics, data modeling, and performance tuning

  • Skilled in Python (Pandas, Numpy, etc.) and data visualization tools (e.g., Tableau, Power BI)

  • Familiarity with cloud data platforms (e.g., AWS, GCP, Azure)

  • Ability to design data schemas and implement analytics tracking strategies

  • Analytical mindset with a focus on impact, efficiency, and scalability

Additional Information

We have competitive compensation.

Work on cool projects based on your interests and skills. We believe in accountability and NOT micro-management.

Company Description

You will join a world-class team of engineers and data scientists from Facebook, Uber, Amazon and Google. We are a fast growing consulting firm based in Toronto with clients ranging from leading startups building impactful technologies to Fortune 500 companies looking to scale their engineering and data capabilities. 

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

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Source & posting history

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Pay

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Location & working pattern

Toronto, ON, Canada

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Status in our records
Active
First seen by us
May 14, 2026
Recorded sightings
129
Last seen by us
Oct 7, 2026
Employer says posted
Sep 5, 2025

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