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

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

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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

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Source & posting history

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Source excerpts

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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.

Open source at jobs.lever.co ↗Read the full description ↓

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

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