Jobs at ShyftLabs

Conduct advanced analytics and statistical modeling for Retail Media Network campaigns, measuring attribution, ROAS, incrementality, and advertising effectiveness. Build predictive models, dashboards, reporting solutions, and automated analytical workflows using SQL, BigQuery, Python, Tableau, and Looker. Translate complex findings into actionable recommendations, manage analytical projects, document methodologies, collaborate with clients, and mentor junior analysts.

Develop and maintain Tableau and Looker dashboards, campaign performance reports, and automated reporting workflows. Analyze large datasets using BigQuery, SQL, Python, and statistical techniques to identify trends and actionable insights. Ensure data quality through profiling, cleansing, validation, and reconciliation. Collaborate with stakeholders to define KPIs, translate requirements into scalable analytical solutions, communicate findings, document workflows, and manage deliverables from development through deployment and maintenance.

Support the SVP and Strategy team with business development initiatives, sales prospecting, market research, customer and competitor analysis, sales presentations, social media content, email campaigns, and lead generation. The intern will help identify new market opportunities, target accounts, decision-makers, and use cases while contributing to pipeline growth and strategic positioning.

Creates graphics, short-form content, pitch decks, social media assets, marketing materials, and internal communications. The intern helps maintain brand consistency, follows and develops visual templates, supports company and client storytelling, contributes to the content calendar, and tracks design and social media trends. The role requires a portfolio, familiarity with design tools, strong visual skills, communication abilities, organization, and the ability to manage multiple deadlines.

Welcomes visitors, manages front-desk communications, schedules meetings, maintains records, handles mail and courier deliveries, manages office supplies, coordinates vendors and building maintenance, supports basic bookkeeping, and assists with administrative projects and events. The role is fully onsite in downtown Toronto and requires strong organization, communication, discretion, multitasking, and Google Workspace proficiency.

Client-facing Product Manager supporting an enterprise Quality AI initiative. Responsibilities include gathering requirements, coordinating business and technical teams, evaluating vendor deliverables, shaping AI-enabled workflows and interfaces, managing UAT and launch readiness, tracking risks and dependencies, and defining KPIs to measure business value. The role bridges Quality stakeholders, data and analytics teams, IT, and implementation vendors to deliver reliable, transparent, and user-friendly AI solutions.

Lead client-facing data architecture initiatives from discovery through production. Design Azure Databricks and Delta Lake platforms, establish medallion architecture, governance, modeling, ingestion, quality, and CI/CD standards, and guide distributed engineering teams. Review architectures, code, pipelines, and data models while advising stakeholders on performance, cost, security, and scalability. Provide hands-on expertise with SQL, Python/PySpark, Airflow, dbt, Unity Catalog, and Databricks-native ingestion technologies.

Design and deliver enterprise GenAI and agentic AI solutions for Fortune 500 clients. Lead discovery sessions, architecture design, client presentations, and technical evaluations while building production-ready applications using LLMs, RAG, agents, Python, LangChain, LangGraph, and Databricks. Integrate structured and unstructured data with enterprise systems, establish evaluation and observability practices, implement responsible AI controls, and support scalable, secure production deployments.

Administer and maintain Oracle Linux and AIX infrastructure, including patching, virtualization, migrations, troubleshooting, performance tuning, and security remediation. Design and maintain Ansible automation across heterogeneous server fleets, lead automation initiatives, support monitoring and ITSM processes, resolve escalations, document procedures, participate in disaster recovery and maintenance activities, and provide on-call support while collaborating across infrastructure, cloud, security, database, network, and application teams.

Build and maintain scalable Databricks ETL/ELT pipelines using Python, PySpark, and SQL. Integrate databases, files, Amazon S3, and REST APIs; manage Delta Lake tables and Unity Catalog; develop dimensional models; schedule and optimize workflows; ensure data quality; tune Spark workloads; and collaborate on production-ready solutions.

Develop and enhance Amazon Connect contact flows, backend services, and React interfaces using AWS, Python, Node.js, and JavaScript. Perform manual, integration, and API testing; track defects; and support security, scalability, and cost efficiency. Provide L2/L3 production support, monitor systems, troubleshoot incidents, document fixes, and participate in on-call rotations. Contribute to Terraform infrastructure and GitLab CI/CD pipelines while integrating CRM and other third-party systems.

Supports and implements Manhattan WMOS warehouse management solutions, gathers and documents requirements, maps business processes, collaborates with stakeholders and technical teams, assists with QA and UAT, deploys production solutions, and provides post-go-live support. Requires expert SQL proficiency, programming knowledge, application troubleshooting experience, and familiarity with deployment and support processes. Experience with Manhattan WMOS SCPP, Manhattan Active, retail, e-commerce, MHE integrations, and robotics is beneficial.

Lead enterprise QA strategy, automation framework development, testing, and release readiness across web, mobile, API, retail, and POS applications. Build and scale Playwright-based E2E frameworks, apply Claude and other generative AI tools to improve test generation and maintenance, oversee test automation and manual testing, mentor QA engineers, manage defect triage and code reviews, and partner with engineering and business teams throughout delivery cycles.

Lead the design, development, and optimization of scalable Databricks ETL/ELT pipelines. Integrate data from databases, S3, files, and REST APIs; implement Delta Lake medallion architecture, Unity Catalog, dimensional models, data quality controls, and Spark performance tuning. Schedule and monitor Databricks workflows, collaborate cross-functionally, and guide engineers while driving technical decisions.

Own strategy, vision, roadmaps, and execution for technically complex data, cloud, and AI products. Lead discovery through launch, define requirements and success metrics, make prioritization and build-versus-buy decisions, and partner with engineering, architecture, data, and AI/ML teams. Serve as the senior product contact for Fortune 500 clients, lead distributed delivery teams, manage dependencies and stakeholders, and mentor junior product professionals.

Develop and maintain Power BI and Looker dashboards, reports, data models, and analytical assets. Analyze complex datasets with SQL and Python, validate data quality, translate stakeholder requirements into actionable insights, and support project milestones. Collaborate with technical and business teams, optimize BI performance, communicate findings, and explore machine learning applications in business analytics.

Own the roadmap and lifecycle of data and AI products, from enterprise discovery and problem definition through delivery, launch, and iteration. Translate business needs into product requirements, partner with engineering, data engineering, and design, define measurable outcomes, lead Agile ceremonies, prioritize feedback-driven improvements, and communicate risks and trade-offs to stakeholders. The role also contributes to product discovery, prioritization, and delivery practices.

Lead design, architecture, and delivery of enterprise-scale data platforms using Databricks and Spark. Architect Lakehouse solutions, build ETL/ELT pipelines, implement IaC and CI/CD, ensure data governance and security, mentor engineers, and partner with Fortune 500 clients from discovery through production.

Design, build, and scale data-driven platforms and systems, focusing on backend and frontend engineering, integrations, and AI capabilities.

The DevOps Engineer will optimize cloud computing solutions, enhance infrastructure performance, ensure high availability, and manage CI/CD tools while collaborating with development teams.