# Senior Data Engineer at ShyftLabs > Hybrid · Canada · Senior · Data engineering · open. Source: https://alderhq.app/jobs/lever%3Ashyftlabs%3A8c5952d9-e223-47bb-bcf5-73e0952eb895 (read 2026-11-07). ## Facts (observed) - Company: [ShyftLabs](https://alderhq.app/companies/shyftlabs) - Location text: Toronto, Ontario - Where it can be done from (inferred): Hybrid · Canada (evidence: "Location: Toronto, Ontario") - Posted: 2026-07-28 (102 days ago) - First seen by alder: 2026-11-02 · last verified: 2026-11-04 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.lever.co/shyftlabs/8c5952d9-e223-47bb-bcf5-73e0952eb895 - Skills listed (inferred): Python, Kafka, AWS, GCP, Azure, Kubernetes, Docker, Terraform, Spark, Airflow, Snowflake, dbt, SQL, LLMs ## Pay and sponsorship - Posted pay: CAD 140k–CAD 180k per year (from the description) - Market band for similar posted roles (Toronto, n 11): p25 CAD 131k, median CAD 135k, p75 CAD 160k ## Description (the employer's text) ### What You'll Be Doing ### Technical Leadership - Lead the architecture, design, and implementation of enterprise-scale data platforms from project inception through production deployment. - Own technical delivery across multiple client engagements while ensuring high-quality engineering standards. - Define solution architecture, technical roadmaps, and implementation strategies aligned with client business goals. - Conduct architecture reviews, code reviews, and establish engineering best practices across project teams. - Mentor and coach Data Engineers while fostering technical excellence and continuous learning. - Serve as the primary technical leader for complex engineering initiatives and critical project decisions. ### Client Partnership - Partner directly with Fortune 500 clients to understand business requirements and translate them into scalable technical solutions. - Lead discovery workshops, architecture sessions, and technical planning meetings with both business and engineering stakeholders. - Present solution designs, delivery plans, and architectural recommendations to technical leadership and executive audiences. - Build trusted relationships with client teams while providing technical guidance throughout project execution. - Support pre-sales activities by contributing technical expertise, solution estimates, and implementation approaches when required. ### Data Engineering & Platform Development - Design, develop, and optimize enterprise-grade data pipelines using the Databricks Unified Analytics Platform. - Build scalable ETL and ELT frameworks capable of processing large-scale structured and unstructured datasets. - Design and implement Lakehouse architectures using Delta Lake and Medallion design patterns. - Develop high-performance Spark applications for batch and real-time data processing. - Integrate data from enterprise applications, APIs, streaming platforms, and cloud storage solutions. - Ensure data quality, integrity, and reliability through automated validation, testing, and monitoring. ### Cloud & DevOps - Architect cloud-native data platforms across AWS, Azure, or Google Cloud Platform. - Implement Infrastructure-as-Code using Terraform or similar technologies. - Build and maintain CI/CD pipelines supporting automated testing and deployment. - Optimize cloud infrastructure for scalability, reliability, security, and cost efficiency. - Monitor platform performance and proactively resolve operational issues. ### Data Governance & Security - Implement enterprise data governance frameworks and security best practices. - Configure Unity Catalog, metadata management, lineage, and role-based access controls. - Ensure compliance with organizational security standards and regulatory requirements. - Promote data observability and operational excellence across production environments ### Cross-Functional Collaboration - Partner closely with Product Managers, Data Scientists, Analytics Engineers, Machine Learning Engineers, and Software Engineers to deliver high-impact data products. - Enable AI and machine learning initiatives through scalable feature engineering pipelines and production-ready datasets. - Contribute reusable frameworks, accelerators, and engineering standards that improve delivery across client engagements. ### What You'll Bring - Bachelor's or Master's degree in Computer Science, Data Engineering, Software Engineering, or a related technical discipline. - 8+ years of experience designing and building enterprise-scale data platforms. - 5+ years of hands-on experience with Databricks and Apache Spark. - Proven experience leading enterprise data engineering projects from architecture through production delivery. - Strong expertise in Python, SQL, and Spark for large-scale data processing. - Deep understanding of Delta Lake, Lakehouse architecture, and modern data platform design. - Experience working with AWS, Azure, or Google Cloud Platform. - Strong knowledge of ETL/ELT frameworks, distributed computing, and data modeling. - Experience implementing CI/CD pipelines and Infrastructure-as-Code. - Strong understanding of data governance, security, metadata management, and data quality practices. - Experience optimizing distributed data processing workloads for performance and cost. - Excellent communication and stakeholder management skills with experience working directly with enterprise clients. - Demonstrated ability to mentor engineers and lead technical initiatives ### Nice to Have - Databricks Certified Professional Data Engineer certification. - Experience with Delta Live Tables, MLflow, Unity Catalog, and Databricks SQL. - Experience with Kafka, Kinesis, Event Hubs, or other streaming technologies. - Hands-on experience with Snowflake, dbt, Airflow, or modern data orchestration tools. - Experience with Kubernetes, Docker, and Terraform. - Knowledge of AI/ML data platforms, Feature Stores, or Retrieval-Augmented Generation (RAG) architectures. - Previous consulting or professional services experience delivering solutions for enterprise clients. - Experience within retail, e-commerce, financial services, logistics, healthcare, or ad-tech environments. ### Salary Range - $140,000 – $180,000 (CAD) --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/lever%3Ashyftlabs%3A8c5952d9-e223-47bb-bcf5-73e0952eb895 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.