Jobs at Unit8

Lead end-to-end Data & AI engagements: define objectives, shape architecture, manage delivery and teams, stay hands-on in implementation, and help grow accounts and pre-sales.

Lead end-to-end Palantir Foundry implementations: architect Ontologies, design pipelines, and build Workshop/Slate applications. Translate business goals into technical roadmaps, drive adoption, mentor juniors, support US business development, and travel to client sites as needed.

Lead customer-facing delivery: design, build, deploy, and maintain data pipelines and AI solutions. Optimize data quality, collaborate with cross-functional engineers and ML experts, support pre-sales and technical advisory, and drive GenAI/LLM initiatives while helping expand Unit8's presence in Canada.

Lead customer-facing delivery of data and AI solutions: design, build, deploy, and maintain data pipelines and infrastructure, optimize data quality, collaborate in cross-functional agile teams, and support pre-sales and technical advisory to drive GenAI and Foundry-based implementations.

Design, build, and maintain data pipelines and infrastructure (with strong Foundry focus). Optimize data quality, collaborate in cross-functional agile teams, support pre-sales and deliver client-facing technical solutions, and help establish Unit8's Canadian presence.

Lead establishment of Unit8's Canadian Data & AI consulting practice: identify high-value AI use cases, assess client AI maturity, shape roadmaps, drive business development, and coordinate delivery with engineers and data scientists to deploy production ML/AI solutions and governance at scale.

Design, build, and maintain data solutions and pipelines on Palantir Foundry. Develop, deploy, and troubleshoot data processing systems, drive data quality and testing, apply Foundry security concepts, collaborate with cross-functional agile teams, and engage with clients. Use Python and PySpark; travel up to 10%.

Design, build, and maintain data solutions on Palantir Foundry. Develop and troubleshoot data pipelines using Python and PySpark, ensure data quality, collaborate in cross-functional agile teams, and engage with clients. Travel up to 10%.

Lead data & AI consulting engagements across the client lifecycle: assess ML/data maturity, identify use cases, design roadmaps, advise on data/platform/cloud/MLOps/governance, collaborate with data scientists and engineers, support business development and thought leadership.

Lead group financial planning, consolidation, forecasting, and treasury for a multi-entity professional services group. Manage a small finance team and outsourced accounting providers, own ERP configuration and data integrity, produce management accounts and board materials, and use AI and analytics tools to streamline reporting, workforce planning, and decision-support analyses.

Lead client engagements to assess data and ML maturity, identify use cases, define implementation roadmaps, advise on data/platform/cloud architecture, and support implementation with data scientists, engineers and IT. Drive consulting practice growth, business development, thought leadership, and contribute to MLOps, governance and analytics center initiatives.

Design, build, maintain, and troubleshoot data pipelines and processing systems for production and analytics. Improve data quality, drive optimization and tooling, and collaborate with engineers, ML experts, and stakeholders in agile teams while engaging with clients.

Design, build, and maintain data solutions on Palantir Foundry. Develop, deploy, and troubleshoot data pipelines using Foundry tools and Python/PySpark. Ensure data quality, security, and collaborate with cross-functional agile teams and clients to deliver data and AI products.

Design, build, deploy, and maintain data pipelines and infrastructure on the Palantir Foundry platform. Optimize and test pipelines to ensure data quality, collaborate with engineers and ML experts in agile teams, troubleshoot production issues, and engage with clients to deliver data-driven solutions.

Lead end-to-end Data & AI engagements: define objectives, design technical architectures, guide and implement solutions, manage teams, ensure delivery quality, and grow client accounts.

Lead consulting engagements to help clients become data-driven: assess data/ML maturity, define use cases and roadmaps, support implementation (MLOps, data/model governance), collaborate with data scientists/engineers, drive business development and thought leadership, and scale the Data & AI consulting practice.