Data Engineer

About Shyft Labs

At Shyft Labs, 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.

Shyft Labs 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.

• 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.

• 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 Dev Ops 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.

• 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.

• $100,000 - $140,000

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.

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.

Shyft Labs 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.