Lead Data Privacy Engineer in Canada

Join the team shaping the future of AI at Scale. Scale builds RL environments: sandboxed replicas of the digital spheres where real knowledge work occurs and built from the operating data of the companies that actually hold it. As the Data Acquisition Lead , you will own the commercial motion that gets us that data end to end. You will figure out which companies sit on the data for the next domain worth owning and then go and get it. This is a zero-to-one function with no playbook. You should be prepared to wear many hats, from thesis-driven dealmaker to hands-on operator to technical translator between commercial and Research teams. You will: Map the supply side. Work backwards from where labs are pushing to the specific organizations holding the underlying data. Build a thesis on which domains are worth owning and in what order. Invent the deal structures. You'll work with Scale’s legal team to define the first version of how these transactions get priced. Close. Own it from cold outreach to signature. Close the loop with the technical side. You need to hold a real conversation about what makes a dataset trainable and become an expert in what makes this underlying data valuable. Build the machine. Do the work by hand first, then turn what you learn into a repeatable pipeline. Ideally, you’d have: 5+ years across some mix of business development, corp dev, commercial strategy, or early-stage GTM. The label matters less than a track record of building a commercial motion that didn't exist before you got there A strong track record of managing important external relationships Strong business judgment and the ability to evaluate partnership value quickly Clear communication skills and comfort working with senior stakeholders Ability to operate independently while staying closely connected to cross-functional teams A practical, hands-on approach to building new functions from the ground up Comfort working in fast-moving, ambiguous environments Experience in

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The vision of the Safety & Customer Care (SCC) team is to foster long-term loyalty to Lyft with every support interaction. If we are successful, a Lyft customer will rarely interact with Lyft Support. But when that interaction occurs, their issue is resolved quickly, effectively, and with true care. For a Lyft customer, their experience of Support should be that “Lyft cares about me and made the experience easy.” As a Data Analytics Lead, you’ll partner directly with cross-functional stakeholders to identify opportunities and design solutions for improving our customers’ support experience. You’ll leverage your analytical expertise to deliver actionable insights and recommendations to drive quality business decisions with customer-facing impact. The ideal candidate is a critical thinker and exceptional problem solver who can build strong relationships with different teams, and who is eager to serve as a leader within the broader Support organization to drive our business forward. Responsibilities Partner with Product, Engineering, Data Science & Analytics, Business Operations and other cross-functional stakeholders to achieve business goals Develop frameworks and scalable processes to drive decision-making and prioritization Define the metrics used to measure the success of strategic initiatives and health of our support platform; build dashboards to track metrics over time Design A/B tests and execute analyses to evaluate the impact of new product features and operational improvements Work closely with cross-functional partners to deliver data-driven insights and actionable recommendations for continuously improving the customer support experience Monitor and diagnose KPI performance and present findings to senior leadership Experience Degree in a quantitative field like statisti

We are looking for a Lead, Data Development, AI Platform to lead the team building and operating the technical platform behind Hootsuite's Analytics MCP. This includes routing infrastructure, orchestration services, agent infrastructure, and data pipelines that enable reliable AI-driven analysis at scale. You will set technical direction for the team, strengthen engineering practices, and translate target architecture and integration standards into secure, production-grade systems that Data Analytics & AI teams can confidently build on. This is a hands-on technical leadership role. You will stay close to the code while owning delivery outcomes, engineering quality, and the team's culture of craft and accountability. You will develop strong, well-reasoned recommendations on how the platform and orchestration architecture should evolve, seek approval at the Senior Manager and Director level, and then guide the team through disciplined execution. You will also partner closely with AI Context & Integration and AI Data Architecture to ensure the platform, context layer, semantic layer, and downstream agent workflows operate as one coherent system. WHAT YOU’LL DO: Lead the design and delivery of the orchestration layer that connects the Analytics MCP platform across its most complex surfaces, including query execution across schemas and models, federated data access between the data warehouse and external source systems, and multi-step agent workflows for cross-functional business processes. Develop clear technical recommendations for platform and orchestration architecture evolution, align those recommendations with Senior Manager and Director-level direction, and guide the team through disciplined execution within the approved architecture. Own the operational reliability, scalability, quality, and observability standards for core Analytics MCP components, including routing and agent infrastructure. Guide the team to build and operate these systems to prod

Overview Scale’s Finance Systems and Automation team is looking for a builder-oriented team member to help design and develop integrations, automations, and AI agents that streamline workflows across Finance, Accounting, People, and Recruiting. In this role, you will work closely with stakeholders across Finance, Accounting, People Operations, and Recruiting to understand their workflows and build integrations, automations, and agentic workflows that reduce manual effort and accelerate execution across these teams. You will leverage our internal data infrastructure, system integration tooling, and emerging AI platforms to architect scalable solutions — from traditional system integrations to intelligent agent-driven workflows — that serve as the foundation for long-term operational efficiency. We’re looking for someone who thrives on connecting systems, automating repetitive processes, and pushing toward more autonomous, AI-assisted operations. You should be comfortable navigating ambiguity, designing solutions that scale, and rigorously validating outcomes end to end. What You’ll Do Design and build agent-driven workflows and automation systems across People Operations, Recruiting, Finance, and Accounting Identify opportunities to replace manual or rules-based processes with agentic workflows Partner with stakeholders to translate business processes into scalable, automated solutions Lead the implementation of end-to-end workflows, from requirements through deployment and validation Automate candidate-to-employee transitions (e.g., Greenhouse → HRIS → provisioning systems) Build workflows to manage employee lifecycle events such as onboarding, transfers, and offboarding Automate approval flows and data synchronization across People, Finance, and Recruiting systems Support accounting and finance workflows through scalable integrations and automation Design and implement the underlying integrations and data flows that enable reliable automation and agent behavior Est

Scale's LLM post-training platform team builds our internal distributed framework for large language model training. The platform powers MLEs, researchers, data scientists, and operators for fast and automatic training and evaluation of LLMs. It also serves as the underlying training framework for the data quality evaluation pipeline. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely with Scale’s ML teams and researchers to build the foundation platform which supports all our ML research and development works. You will be building and optimizing the platform to enable our next generation LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework. Collaborate with ML and research teams to accelerate their research and development, and enable them to develop the next generation of models and data curation. Research and integrate state-of-the-art technologies to optimize our ML system. Ideally you’d have: Passionate about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Experience with post-training methods like RLHF/RLVR and related algorithms like PPO/GRPO etc. Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills to operate in a cross functional team environment. Nice to haves: Demonstrated expertise in post-training methods and/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity,

About the Team Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and fi nancial reporting. Team serves as the foundation for decision-making at DoorDash. About the Role DoorDash is looking for a Sta ff Software Engineer,Data to be a technical lead and help architect and scale our data reliability, data infrastructure, automation and tools to meet growing business needs. You’re excited about this opportunity because you will... Own critical data systems that support multiple products/teams Develop, implement and enforce best practices for data infrastructure and automation Design, develop and implement large scale, high volume, high performance data models and pipelines for Data Lake and Data Warehouse Improve the reliability and scalability of our Ingestion, data processing, ETLs, Reporting tools and data ecosystem services Manage a portfolio of data products that deliver high-quality, trustworthy data Help onboard and support other engineers as they join the team We’re excited about you because... 8+ years of professional experience as a hands-on engineer and technical leader leading multiple projects 6+ years experience working in data platform and data engineering or a similar role You have proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software Pro fi ciency in programming languages such as Python/Kotlin/Scala 4+ years of experience in ETL orchestration and work fl ow management tools like Air fl ow Expert in database fundamentals, SQL, data reliability practices and distributed computing 4+ years of experience with the Distributed data/similar ecosystem (Spark, Presto) and streaming technologies such as Kaa/Flink/Spark Streaming Excellent communication skills and experience working

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. Data is at the foundation of DoorDash success. The Data Engineering team builds database solutions for various use cases including reporting, product analytics, marketing optimization and financial reporting. By implementing data structures and data warehouse architecture, this team serves as the foundation for decision-making at DoorDash. The focus extends to enhancing the developer experience by creating tools that support the organization's high-velocity demands. To lead the growing team of Data engineers we are looking for managers who are passionate about Data and are thought leaders in coaching, guiding and leading teams to make Data a winning edge for DoorDash. About the Role DoorDash is looking for a Data Engineering Manager to guide the development of enterprise-scale data solutions. This manager will also act as a technical expert on all things related to data architecture to empower the greater community of data engineers, data scientists, and DoorDash partners. Your focus extends to fostering an engineering culture of excellence, empowering engineers to deliver reliable, flexible solutions at scale. Additionally, you'll play a pivotal role in building and nurturing a top-performing team, driving innovation and success in a dynamic, fast-paced environment. You must be located in San Francisco, CA, Sunnyvale, CA, or Seattle, WA for this hybrid position. You’re excited about this opportunity because you will… You are a people leader. You thrive in hiring, building, growing and nurturing impactful business focused data teams You are a technology leader. You drive the technical and strategic vision for the embedded pods and foundational enablers to meet current and future needs for scale and interoperability You strive for continuous improvement of data architecture and development process You think of quick wins

EnCharge AI is a leader in advanced AI hardware and software systems for edge-to-cloud computing. EnCharge’s robust and scalable next-generation in-memory computing technology provides orders-of-magnitude higher compute efficiency and density compared to today’s best-in-class solutions. The high-performance architecture is coupled with seamless software integration and will enable the immense potential of AI to be accessible in power, energy, and space constrained applications. EnCharge AI launched in 2022 and is led by veteran technologists with backgrounds in semiconductor design and AI systems. Lead DFT Engineer Job Description: Developing silicon for edge-to-cloud computing isn't just about speed; it’s about balancing high-performance data processing with extreme power efficiency and reliability in remote environments. As the Design for Test (DFT) Lead, you will be the architect of our testing strategy, ensuring our data center chips are flawlessly manufacturable and resilient enough for edge deployment. Key Responsibilities: Architectural Leadership: Define and implement the end-to-end DFT architecture for complex SoCs, including Hierarchical DFT, Scan compression, Boundary Scan and MBIST. Edge-Specific Reliability: Develop strategies for In-System Test (IST) and power-on self-test (POST) to ensure chip health in remote edge data centers. Implementation & Flow: Oversee scan insertion, ATPG (Stuck-at, Transition, Path Delay), and Memory /Logic BIST. Cross-Functional Synergy: Collaborate with Design, Physical Design, and Yield teams to ensure high test coverage while minimizing area overhead and power impact as well as timing analysis . Post-Silicon Validation: Lead the bring-up and debug phase on ATE (Automated Test Equipment) to root-cause silicon failures and optimize test time. Technical Requirements: Experience: 12+ years in DFT, with at least 2 years in a leadership or principal role. Bachelor’s degree in a related field. Tools:

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Data is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve performing rigorous product deep dives, identifying opportunities for product enhancements, and measuring the impact of product changes. The Airports team, within the Driver organization, focuses on the airport marketplace and the unique products designed for this use case. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experience and have unique dynamics. As an Analytics Lead on the Airport team, you will collaborate with our team of engineers, product managers, and designers to conduct thorough data deep dives on airport performance, challenge our current strategy, and recommend enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product and marketplace changes, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as: How should we determine pricing and earnings for airport rides? Who are our current airport drivers and what segment can we focus on to grow our supply? How does this strategy interact with driver bonuses? Which airports are underperforming and which key metrics can we use to identify and classify airport performance? What targets should we set for these key metrics and how do we efficiently monitor these metrics? What is driving high cancellation rates today and which types of riders/drivers are cancelling? What product changes can we implement to reduce cancellation rates? How are riders and drivers using different ride modes at airports, and how do we design

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. Lyft is hiring a Senior Financial Data Analyst to lead the Reporting sub-team within Finance Data & Insights. This sub-team is core to ensuring all key Run the Business (RTB) financial reports are complete, accurate, and operationally reliable on a day-to-day basis. The mandate is two-fold: build repeatable systems, playbooks, and documented workflows that reduce reactive work, and own the primary stakeholder relationships for RTB work across teams. This is a high-visibility role that combines hands-on ownership of critical reporting with team leadership and process-building. Responsibilities: Own all RTB and Compliance reporting (tax, airports, audit requests, etc.), ensuring accuracy, completeness, and operational reliability Build and maintain process documentation, checklists, and operational playbooks that make reporting workflows repeatable and resilient Receive and operationalize reports stabilized by Finance Data Products, integrating them into day-to-day RTB reporting operations Reduce fire-drill, ad-hoc response patterns by replacing them with documented, recurring workflows and automation Identify and drive automation opportunities across RTB reporting processes to improve efficiency, reduce manual effort, and further reduce ad-hoc work Own primary stakeholder relationships for RTB work, serving as the go-to point of contact across teams Lead large-scale, cross-functional initiatives with significant autonomy — from problem definition through execution — proactively communicating progress and risks to stakeholders and management Proactively identify risks, gaps, and opportunities for improvement within RTB reporting and drive initiatives to address them Experience: BA/BS with 5+ years of experience in finance, accounting, business, consulting, or analytics Advanced proficiency in

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Growth Products team drives rider and driver acquisition to scale the business and balance the marketplace. We specialize in incentive and messaging targeting, budget optimization, and paid media measurement, and move rapidly to test new ideas and products. As a Data Scientist expert in causal inference and marketing mix models (MMM), you will lead our efforts to measure and optimize investments across marketing channels. Responsibilities: Deliver results across the entire lifecycle of data science solutions for Growth: from defining the problem with cross-functional stakeholders to deploying production models that address key business problems. Own complex domains and develop long-term roadmaps to maximize business impact. Build statistical pipelines, write production code, and design/analyze experiments. Participate in the science on-call rotation to ensure automated campaigns operate successfully. Experience: Advanced degree in statistics, economics, mathematics, or equivalent industry experience. 4+ years of industry experience in causal inference or data science. Proven ability to apply statistics to unstructured problems and deliver measurable results. Deep technical expertise in causal inference and tackling challenging measurement problems. Expertise in marketing mix modeling is highly preferred. Expertise in SQL and experience with large-scale data platforms. Proficiency in Python and working within production coding environments. Benefits: Great medical, dental, and vision insurance options with additional programs available when enrolled Mental health benefits Family building benefits Child care and pet benefits 401(k) plan with company match to help save for your future In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team membe

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. Our Core Data Engineering team is responsible for designing and building all foundational datasets used across Robinhood and within our operational business areas. We build the foundational data models and core data layers that are consumed by downstream users, ensuring high data quality and reliability. We also develop internal data and AI tooling that enables teams across the company to scale their data development workflows efficiently. Our team collaborates with engineering, product, brokerage, crypto, and marketing teams to expand and grow Robinhood's products around the world ! We also partner with Machine Learning teams to build robust training datasets that power intelligent product features. As the Engineering Manager for our Toronto Data Engineering team, you will lead a team of exceptional engineers and drive the execution of key data initiatives. In this role, you will balance technical leadership with people management, dedicating approximately 60% of your time coaching and 40% to hands-on technical contributions, such as code and architecture reviews. You will drive roadmap planning and establish clear goals for the team, particularly as we expand into new mark

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: At Reddit we continue to grow our teams with the best talent. We're completely remote friendly . Team Description: The Marketing Science team at Reddit leverages data to maximize the impact of Reddit’s own marketing investments. We serve as the engine behind our growth, using advanced experimentation, causal inference, and econometrics to understand what drives users to Reddit and what brings advertisers to our platform. We work at the intersection of brand building and performance marketing, ensuring every dollar spent is an investment in the long-term health of our ecosystem. Role Description: Reddit is looking for a highly experienced Staff Data Scientist to lead the strategy and technical execution of our Marketing Intelligence efforts. In this role, you will be the primary architect of how we measure and optimize Reddit’s marketing spend. You will focus on two critical flywheels: B2B Marketing (acquiring and retaining advertisers) and B2C Growth (acquiring and engaging new Redditors). This is a high-autonomy, high-impact role where you will set the long-term strategic goals for Reddit’s marketing measurement, influencing senior leadership and defining how we value our brand and performance efforts. Responsibilities: Set Long-Term Marketing Strategy: Define the 2–3 year technical roadmap for marketing measurement. Establish the "North Star" metrics and frameworks that determine how Reddit allocates hundreds of millions in marketing budget. Optimize Marketing ROI: Build and refine Media Mix Models (MM

At Scale, we develop reliable AI systems for the world’s most important decisions. Scale’s product marketing team is responsible for developing and executing strategies that drive awareness and engagement for Scale’s offerings amongst our core audiences. We take a data-driven approach to understand our customers’ needs and challenges, ensuring that their voices are reflected in product development and messaging. We partner closely with product, engineering, research, sales, comms, and the broader marketing team to create a cohesive customer experience across all our channels. We aim to provide valuable insights and resources that help our customers execute on their AI transformation journey. This role will focus on developing and optimizing vertical-specific messaging and content for Scale’s applications business to ensure our messaging resonates with core buyers across verticals. The ideal candidate combines strategic thinking with hands-on execution. You will: Develop clear, compelling messaging for enterprise offerings tailored to key personas within target verticals Create marketing assets, including slide decks, videos, blog posts, and one-pagers, that effectively communicate our value propositions to vertical leaders and support our sales team’s pursuits Lead positioning and sales enablement efforts to drive awareness and engagement for Scale’s offerings. Drive cross-functional marketing programs around target verticals, in conjunction with product, engineering, sales, and growth marketing to create a cohesive customer experience and contribute to pipeline targets Collaborate with field marketing and events teams to develop vertical-specific event strategies, content, and experiences that drive engagement within customer and target accounts Drive customer marketing efforts, creating both strategy and tactics to maximize the value Scale and customers get from our shared success, including case studies, testimonials, visual assets and event particip

Come join our legal team to work on the most exciting legal, policy, and operational issues at the leading edge of AI. We're seeking strong product lawyers with specialized expertise in intellectual property law. As product counsel, you will advise on all legal aspects of product development, launch, and operations - including regulatory compliance, user terms, and risk management - while bringing deep expertise in your specialized legal area. The ideal candidate will have deep subject matter expertise in intellectual property law, a technology background, and a demonstrable history of providing practical product counsel to solve complex, time-sensitive problems in close partnership with cross-functional teams. This role reoprts to the Associate General Counsel, IP & Product. You will: Strategic Product Advice: Lead IP strategy for product development, embedding IP protection into the full product lifecycle from conception to commercialization, while also advising on related product and regulatory matters in collaboration with the broader legal team. Cross-Functional Collaboration: Partner with Research, Product, Engineering, Operations, Communications, and Marketing teams to mitigate IP risks in product development, data licensing, and open-source governance. IP Counsel: Support management of Scale's worldwide IP portfolio including patents and trademarks; assist with patent prosecution and trademark registration and enforcement. Risk Mitigation: Advise on third-party, synthetic, and open-source data and models, ensuring compliance with licensing requirements; design open-source governance policies. Agreements: Support drafting and negotiation of commercial agreement provisions involving intellectual property. Specialized Expertise: Provide counsel on machine learning, robotics, and other technical areas, with ability to engage effectively with technical teams on complex engineering and product issues. Training: Develop and deliver IP and data licensing trainin