{"id":720981,"url":"https://alion.io/job/shyftlabs-data-engineer-3","title":"Data Engineer","company":{"id":685982,"name":"Shyftlabs","domain":"shyftlabs.io","url":"https://alion.io/company/shyftlabs","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"A","score":91,"open_postings":25,"ghost_share":0,"stale_share":0.36,"repost_share":0,"time_to_fill_p50_days":39,"computed_at":"2026-11-01T06:10:25Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Toronto, Canada"],"countries":["CA"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":100000,"max":140000,"currency":"CAD","period":"year","gross":null,"usd_annual":99696},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"ETL/ELT","optional":false},{"name":"GCP","optional":false},{"name":"Python","optional":false},{"name":"Scala","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false},{"name":"Amazon Kinesis","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Docker","optional":true},{"name":"Feature Store","optional":true},{"name":"Kubernetes","optional":true},{"name":"Looker","optional":true},{"name":"MLFlow","optional":true},{"name":"Power BI","optional":true},{"name":"Tableau","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-04-01T19:40:43Z","employer_posted_date":"2026-04-01","last_verified_at":"2026-11-01T10:12:30Z","board_verified":true,"closed_at":null,"days_open":213,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":213},"description":"About ShyftLabs\nAt 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.\nThe Opportunity\nShyftLabs 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.\nWhat You'll Be Doing\nDesign, implement, and optimize big data pipelines in Databricks.\n\nDevelop scalable ETL workflows to process large datasets.\n\nLeverage Apache Spark for distributed data processing and real-time analytics.\n\nImplement data governance, security policies, and compliance standards.\n\nOptimize data lakehouse architectures for performance and cost-efficiency.\n\nCollaborate with data scientists, analysts, and engineers to enable advanced AI/ML workflows.\n\nMonitor and troubleshoot Databricks clusters, jobs, and performance bottlenecks.\n\nAutomate workflows using CI/CD pipelines and infrastructure-as-code practices.\n\nEnsure data integrity, quality, and reliability in all pipelines.\n\nWhat You Bring\nBachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.\n\n5+ years of hands-on experience with Databricks and Apache Spark.\n\nProficiency in SQL, Python, or Scala for data processing and analysis.\n\nExperience with cloud platforms (AWS, Azure, or GCP) for data engineering.\n\nStrong knowledge of ETL frameworks, data lakes, and Delta Lake architecture.\n\nExperience with CI/CD tools and DevOps best practices.\n\nFamiliarity with data security, compliance, and governance best practices.\n\nStrong problem-solving and analytical skills with an ability to work in a fast-paced environment.\n\nNice to Have\nDatabricks certifications (e.g., Databricks Certified Data Engineer, Spark Developer).\n\nHands-on experience with MLflow, Feature Store, or Databricks SQL.\n\nExposure to Kubernetes, Docker, and Terraform.\n\nExperience with streaming data architectures (Kafka, Kinesis, etc.).\n\nStrong understanding of business intelligence and reporting tools (Power BI, Tableau, Looker).\n\nPrior experience working with retail, e-commerce, or ad-tech data platforms.\n\nSalary Range\n$100,000 - 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