Back to jobs

Data Engineer

Toronto, Ontario

Pay
$100,000–140,000/yearAnnual period assumed — pay source
Salary Range $100,000 - $140,000 Why You’ll Love Working at ShyftLabs
Read the full posting
Work setup
Unconfirmed
Employment
Full-time — employment source
Employment type Full-Time
Read the full posting
Apply at Shyftlabs

What you’ll bring

All qualifications

Core experience

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
  • Hands-on experience with MLflow, Feature Store, or Databricks SQL.
  • 5+ years of hands-on experience with Databricks and Apache Spark.
  • Experience with streaming data architectures (Kafka, Kinesis, etc.).
  • Proficiency in SQL, Python, or Scala for data processing and analysis.
  • Strong understanding of business intelligence and reporting tools (Power BI, Tableau, Looker).
Qualification wording
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
Hands-on experience with MLflow, Feature Store, or Databricks SQL.
5+ years of hands-on experience with Databricks and Apache Spark.
Experience with streaming data architectures (Kafka, Kinesis, etc.).
Proficiency in SQL, Python, or Scala for data processing and analysis.
Strong understanding of business intelligence and reporting tools (Power BI, Tableau, Looker).
Education & alternatives
What You Bring - Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. - 5+ years of hands-on experience with Databricks and Apache Spark.

Tools in this posting

  • Python
  • Scala
  • SQL
  • AWS
  • Azure
  • Databricks
  • Delta
  • Docker
  • Google Cloud (GCP)
  • Kafka
  • Kubernetes
  • MLflow
  • Spark
  • Tableau
  • Power BI
  • Looker
  • Terraform
Source — Tool mentions in context
The Opportunity ShyftLabs is seeking a skilled Data Engineer to support in designing, developing, and optimizing big data solutions using the Databricks Unified Analytics Platform. This role requires strong expertise in Apache Spark, SQL, Python, and cloud platforms (AWS/Azure/GCP). The ideal candidate will collaborate with cross-functional teams to drive data-driven insights and ensure scalable, high-performance data architectures. What You'll Be Doing
- 5+ years of hands-on experience with Databricks and Apache Spark. - Proficiency in SQL, Python, or Scala for data processing and analysis. - Experience with cloud platforms (AWS, Azure, or GCP) for data engineering.
- Databricks certifications (e.g., Databricks Certified Data Engineer, Spark Developer). - Hands-on experience with MLflow, Feature Store, or Databricks SQL. - Exposure to Kubernetes, Docker, and Terraform.
- Proficiency in SQL, Python, or Scala for data processing and analysis. - Experience with cloud platforms (AWS, Azure, or GCP) for data engineering. - Strong knowledge of ETL frameworks, data lakes, and Delta Lake architecture.
What You'll Be Doing - Design, implement, and optimize big data pipelines in Databricks. - Develop scalable ETL workflows to process large datasets.
- Collaborate with data scientists, analysts, and engineers to enable advanced AI/ML workflows. - Monitor and troubleshoot Databricks clusters, jobs, and performance bottlenecks. - Automate workflows using CI/CD pipelines and infrastructure-as-code practices.
- Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field. - 5+ years of hands-on experience with Databricks and Apache Spark. - Proficiency in SQL, Python, or Scala for data processing and analysis.
Nice to Have - Databricks certifications (e.g., Databricks Certified Data Engineer, Spark Developer). - Hands-on experience with MLflow, Feature Store, or Databricks SQL.
- Experience with cloud platforms (AWS, Azure, or GCP) for data engineering. - Strong knowledge of ETL frameworks, data lakes, and Delta Lake architecture. - Experience with CI/CD tools and DevOps best practices.
- Hands-on experience with MLflow, Feature Store, or Databricks SQL. - Exposure to Kubernetes, Docker, and Terraform. - Experience with streaming data architectures (Kafka, Kinesis, etc.).
- Exposure to Kubernetes, Docker, and Terraform. - Experience with streaming data architectures (Kafka, Kinesis, etc.). - Strong understanding of business intelligence and reporting tools (Power BI, Tableau, Looker).
- Develop scalable ETL workflows to process large datasets. - Leverage Apache Spark for distributed data processing and real-time analytics. - Implement data governance, security policies, and compliance standards.
- Experience with streaming data architectures (Kafka, Kinesis, etc.). - Strong understanding of business intelligence and reporting tools (Power BI, Tableau, Looker). - Prior experience working with retail, e-commerce, or ad-tech data platforms.

About Shyftlabs

Since 2020, we’ve been helping Fortune 500 companies unlock growth with cutting-edge digital solutions that transform industries and create measurable business impact.

In the employer’s words · Read in context

Job description

View original posting ↗

About ShyftLabs

At ShyftLabs, we live and breathe data. Since 2020, we’ve been helping Fortune 500 companies unlock growth with cutting-edge digital solutions that transform industries and create measurable business impact. We’re growing fast and we’re looking for passionate problem-solvers who are ready to turn big ideas into real outcomes.


The Opportunity

ShyftLabs is seeking a skilled Data Engineer to support in designing, developing, and optimizing big data solutions using the Databricks Unified Analytics Platform. This role requires strong expertise in Apache Spark, SQL, Python, and cloud platforms (AWS/Azure/GCP). The ideal candidate will collaborate with cross-functional teams to drive data-driven insights and ensure scalable, high-performance data architectures.

What You'll Be Doing

  • Design, implement, and optimize big data pipelines in Databricks.

  • Develop scalable ETL workflows to process large datasets.

  • Leverage Apache Spark for distributed data processing and real-time analytics.

  • Implement data governance, security policies, and compliance standards.

  • Optimize data lakehouse architectures for performance and cost-efficiency.

  • Collaborate with data scientists, analysts, and engineers to enable advanced AI/ML workflows.

  • Monitor and troubleshoot Databricks clusters, jobs, and performance bottlenecks.

  • Automate workflows using CI/CD pipelines and infrastructure-as-code practices.

  • Ensure data integrity, quality, and reliability in all pipelines.

What You Bring

  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.

  • 5+ years of hands-on experience with Databricks and Apache Spark.

  • Proficiency in SQL, Python, or Scala for data processing and analysis.

  • Experience with cloud platforms (AWS, Azure, or GCP) for data engineering.

  • Strong knowledge of ETL frameworks, data lakes, and Delta Lake architecture.

  • Experience with CI/CD tools and DevOps best practices.

  • Familiarity with data security, compliance, and governance best practices.

  • Strong problem-solving and analytical skills with an ability to work in a fast-paced environment.

Nice to Have

  • Databricks certifications (e.g., Databricks Certified Data Engineer, Spark Developer).

  • Hands-on experience with MLflow, Feature Store, or Databricks SQL.

  • Exposure to Kubernetes, Docker, and Terraform.

  • Experience with streaming data architectures (Kafka, Kinesis, etc.).

  • Strong understanding of business intelligence and reporting tools (Power BI, Tableau, Looker).

  • Prior experience working with retail, e-commerce, or ad-tech data platforms.

Salary Range

  • $100,000 - $140,000
Why You’ll Love Working at ShyftLabs
Hybrid Flexibility: 3 days per week in our downtown Toronto office. This role is also open to candidates based out of the Calgary area.
Comprehensive Benefits: 100% coverage for health, dental, and vision insurance for you and your dependents from day one.
Growth & Learning: Continuous learning opportunities and influence over technical direction.
 
Inclusion at ShyftLabs
We’re building something big, and we want you on the journey with us. If you’re ready to use data and innovation to make an impact, apply today and let’s grow together.
 
ShyftLabs is an equal-opportunity employer committed to creating a safe, diverse, and inclusive environment. We encourage applicants of all backgrounds including ethnicity, religion, disability status, gender identity, sexual orientation, family status, age, and nationality to apply. If you require accommodation during the interview process, let us know and we’ll be happy to support you.

Employment type

Full-Time

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on jobs.lever.co. The employer’s form will show what is required.

Already applied? Track this application

Source & posting history

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
Salary Range $100,000 - $140,000 Why You’ll Love Working at ShyftLabs
Location & working pattern

Toronto, Ontario

Why You’ll Love Working at ShyftLabs Hybrid Flexibility: 3 days per week in our downtown Toronto office. This role is also open to candidates based out of the Calgary area. Comprehensive Benefits: 100% coverage for health, dental, and vision insurance for you and your dependents from day one.
Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

Status in our records
Active
First seen by us
Apr 14, 2026
Recorded sightings
136
Last seen by us
Oct 7, 2026
Employer says posted
Apr 1, 2026

These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.

Report an error

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.