ShyftLabs Announces Official OpenAI Partnership
ShyftLabs
ShyftLabs announced that it became an official OpenAI partner as it expands enterprise AI solutions and production deployments.
Read articleRemote eligible location: Canada.
We are looking for an experienced and versatile Data Engineer to join our dynamic and fast-growing team. If you are passionate about data, solving complex problems, and working directly with enterprise stakeholders to translate business needs into scalable technical solutions, this role could be the perfect fit.
ShyftLabs is a growing data product company that was founded in early 2020 and works primarily with Fortune 500 companies. We deliver digital solutions built to help accelerate the growth of businesses across various industries by focusing on creating value through innovation.
In addition to strong technical expertise, we are seeking someone with strong business awareness and the ability to lead client and stakeholder communication. The ideal candidate will be comfortable collaborating with enterprise-level clients, translating complex technical concepts into business outcomes, and ensuring alignment between engineering execution and strategic objectives.
Design, build, and maintain scalable and reliable batch and real-time ETL/ELT data pipelines using cloud services such as GCP Dataflow, Cloud Functions, Pub/Sub, and Cloud Composer.
Architect and implement robust data infrastructure capable of handling high-volume data ingestion and processing.
Develop and manage our central data warehouse in Google BigQuery.
Design and implement data models, schemas, and table structures optimized for performance, scalability, and long-term maintainability.
Write clean, efficient, and maintainable SQL and Python code to transform raw data into curated, analysis-ready datasets.
Build reliable transformation workflows that support analytics, reporting, and data science initiatives.
Monitor, troubleshoot, and optimize data infrastructure to ensure high performance, reliability, and cost efficiency.
Implement BigQuery best practices, including partitioning, clustering, query optimization, and materialized views.
Build and maintain curated data models that serve as the “source of truth” for business intelligence and reporting.
Ensure data is optimized and readily accessible for BI tools such as Looker and other analytics platforms.
Implement automated data quality checks, validation rules, and monitoring frameworks to ensure the integrity and reliability of data pipelines and warehouse systems.
Establish processes for data governance, observability, and lineage tracking.
Work closely with software engineers, data analysts, and data scientists to understand their data requirements and provide the necessary infrastructure and data products.
Lead and support client and stakeholder communication, working with enterprise clients to translate business needs into scalable data solutions.
Partner with product teams and leadership to ensure that technical data solutions align with business strategy and client expectations.
Take ownership of data platforms and architecture decisions, helping shape the future direction of our analytics and data infrastructure.
Identify opportunities to improve data reliability, automate workflows, and generate new insights through data.
Contribute to a collaborative, high-performing engineering culture with strong communication and teamwork.
5+ years of hands-on experience in data engineering, data integration, or data platform development.
Degree in Computer Science, Engineering, Mathematics, or related STEM discipline.
Strong programming and query skills in SQL and Python.
Experience working with distributed version control systems such as Git in an Agile/Scrum environment.
Experience designing and orchestrating ETL pipelines, particularly with Databricks.
Experience working within cloud environments (GCP, AWS, or Azure).
Experience with database systems such as MongoDB and Elasticsearch.
Strong understanding of data warehousing and dimensional modeling methodologies.
Hands-on experience with Airflow and Hadoop.
Experience using Docker for containerized workflows and reproducible environments.
Ability to identify opportunities to improve data quality, reliability, and automation.
Strong business awareness and communication skills, with the ability to collaborate with both technical teams and business stakeholders.
Experience within the retail industry is a plus.
Master’s degree in Computer Science, Engineering, or related discipline.
Experience working with enterprise-scale data platforms and Fortune 500 clients.
Familiarity with Druid and its Python API, including Kafka integrations.
Strong experience using Apache Spark for large-scale data processing.
Experience designing real-time streaming data architectures.
Experience working with AI-driven platforms, data infrastructure supporting AI/ML systems, or agentic AI workflows
This Data Engineer role builds and operates scalable batch and streaming data infrastructure, centered on Google Cloud and BigQuery. The work combines hands-on pipeline and warehouse development with enterprise stakeholder communication and alignment of data solutions to business needs.
ShyftLabs builds enterprise data and AI systems for organizations in retail, healthcare, financial services, energy, government, manufacturing and supply chain. Its work spans applied intelligence, data infrastructure and engineering, activation and analytics, and governance and security. The company also develops Continuum, an agentic AI platform comprising an open-source agent runtime, Aura for intelligent model routing, and Provenance for governance and observability. ShyftLabs says it has launched more than 50 enterprise solutions and employs more than 250 data and AI specialists across locations including Toronto, New York, Dubai and India.
ShyftLabs offers candidates exposure to enterprise AI, data engineering and agentic AI projects used by major retailers, healthcare organizations and public-sector clients. The company says it has more than 250 data and AI specialists and has launched over 50 enterprise solutions. Its Continuum platform includes an open-source agent runtime, intelligent model routing and AI governance, creating work across agents, distributed systems, data infrastructure and security. Current roles reference Python, Databricks, Spark, AWS, Azure, GCP, Terraform and Kubernetes. Job postings also highlight technical ownership, mentoring, professional development, employer-paid health benefits in Canada and hybrid flexibility for applicable roles.
Programming Language
Backend Framework
Frontend Framework
Database
Database
Data and AI Platform
Data Processing
Data Processing
Data Platform
Cloud Data Platform
Data Transformation
Data Orchestration
Cloud Infrastructure
Cloud Infrastructure
Cloud Infrastructure
Infrastructure as Code
Containers
Container Orchestration
Workflow Orchestration
Vector Database
Vector Database
AI Observability
Machine Learning Platform
Cloud Data Warehouse
Founder and CEO of ShyftLabs with a background in analytics, product and retail technology. Before founding ShyftLabs, Khandelwal worked at companies including Jet.com, Citi and Evernote and co-founded Minoan. He holds an MS in Operations Research from Columbia University and a BE in Computer Science from Panjab University.
Leads security and privacy initiatives at ShyftLabs and contributes to the company's enterprise AI governance work. His background includes software engineering, application security, penetration testing and cloud security, with prior cybersecurity experience at KPMG and professional certifications across AWS and Google Cloud.
Leads consulting and services at ShyftLabs, helping translate enterprise business requirements into data, AI and digital transformation programs. His background includes product management, consulting and entrepreneurship, including co-founding healthcare technology venture InsightHx.
ShyftLabs
ShyftLabs announced that it became an official OpenAI partner as it expands enterprise AI solutions and production deployments.
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ShyftLabs introduced Aura, a model-routing layer within Continuum that can route AI requests across more than 250 models and 45 providers according to quality, latency, cost and policy requirements.
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ShyftLabs disclosed its work on the data foundation supporting MAC Cosmetics' Shopify storefront, including real-time activation, consent and privacy enforcement and unified customer profiles.
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ShyftLabs hosted AgentShyft during Toronto Tech Week, where developers built production-oriented agentic AI applications using the company's Continuum framework.
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