Data Governance Analyst Banking in Canada

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 seeking a Financial Analyst on our Corporate FP&A team, focused on consolidated P&L reporting, financial forecasting, and data quality across the team's core reporting processes. The ideal candidate will bring natural curiosity, financial rigor, and an exceptional eye for detail to the team, driving accurate, timely financial analysis in support of strategic decision making at Lyft. Responsibilities: Own recurring data management processes that support team-wide reporting and forecasting, with a strong focus on data accuracy and integrity Own consolidated P&L reporting, ensuring timely and accurate updates Perform thorough quality checks on financial data and reporting outputs, catching and resolving issues before they reach stakeholders Support financial forecasting and reporting cycles, including scenario analysis to help inform business decisions Support reporting and variance analysis for specific areas of the business, partnering closely with business stakeholders Partner with finance systems teams to support data governance and process improvements Serve as a point person for ad hoc analysis and special projects Identify and drive opportunities to improve reporting and planning processes Experience: Bachelor's degree in Finance, Accounting, Economics, or a related field, or equivalent practical experience 3-5+ years of experience in financial planning and analysis, ideally within a corporate finance or consolidations environment Exceptional attention to detail with a strong quality-control mindset — able to catch and resolve data or formatting issues before deliverables go out Working knowledge across all three core financial statements (P&L, Cash Flow, and Balance Sheet) Proficiency in Gsheets/Excel for financial modeling and data management Proficiency in Google Slides

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

Solution Architect Sigma Computing The SA role has evolved. Here’s the version we’re hiring for. The SA job in 2026 is not the SA job in 2023. Three things now sit at the center of how we evaluate this role. This hire has to do all three at a senior level, with the architectural depth to back it up. 1. Use AI every day to do the job better. If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are. We expect this hire to treat AI tooling as default infrastructure, not novelty. Come with a point of view on what you run, why, and how you use it to compress weeks of work into days. 2. Sell AI into the account. Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what. You have to be fluent. You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns. You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call. You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs. 3. Sell against AI. Every enterprise deal has AI competition in it. Sometimes it is Databricks Genie. Sometimes it is Snowflake Cortex Analyst. Sometimes it is a systems integrator pitching a bespoke agent built over the weekend. You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving. You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls. About Sigma Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, an

About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. The Core Data Platform organization owns all the infrastructure necessary to run an operationally efficient analytical data stack. About the Roles The Data Platform team spans data mobility frameworks, ingestion, infrastructure, tools, and governance. Together, they design and operate scalable compute and ingestion frameworks using technologies such as Spark, Flink, Kafka, Airflow, and modern lakehouse solutions, while also building abstractions and tools that simplify data workflows for engineers, analysts, and ML practitioners. In parallel, these teams establish strong data quality, cataloging, privacy, and compliance standards to ensure trust in analytics and regulatory adherence. As relatively high-impact teams, they offer engineers the opportunity to shape the roadmap, influence core platform decisions, and directly enable DoorDash’s business-critical insights and real-time personalization capabilities. You must be located in San Francisco, CA, Sunnyvale, CA, Seattle, WA, or New York, NY. You're excited about this opportunity because you will… Drive vision & strategy for building the frameworks charter and position it to handle the challenges of a rapidly growing business. Scale the analytical platform for the increasing amounts of data and use cases. You will bring your expertise in building and operating high scale systems with a focus on reliability, scalability and cost efficiency. Collaborate with stakeholders building solutions on top of the platform Foster a positive and supportive work culture, upleveling others. We're excited about you because you have… B.S., M.S., or PhD. in Computer Science or equivalent. 2+ years of industry experience at our I4 level, 5+ years of industry experience at our I5 level Proficiency in using AI coding tools (e.g., Claude Code, Codex, Cursor) in th

About Prophecy Prophecy is building the next generation AI-powered data prep and analysis platform. Our platform enables business analysts and data teams to transform raw data into reliable, production-ready datasets and insights faster, using modern data infrastructure and AI-driven capabilities. We work with leading enterprises to simplify how organizations prepare, analyze, and operationalize data, while maintaining strong governance, security, and operational control. Our mission is to make it dramatically easier for organizations to turn complex data into trusted insights that drive decisions. About the Roles We are looking for a Director of Strategic Partnerships who can do both: drive revenue through Prophecy's partner ecosystem, and build an effective partner program. This is an early-stage, high-ownership motion, the playbook is still being written, and you'll have real influence over how we engage partners, what good looks like for partner-sourced pipeline, and how we build durable co-sell relationships with Snowflake, Databricks, GCP field and partner teams. You will sit at the intersection of sales, partnerships, and strategy, owning partner performance while building the programs and processes that scale it. You'll work directly with our AEs and SEs to bring partners into deals at the right moments, and you'll serve as the primary point of contact for our strategic cloud and ecosystem partners. What You’ll Own Partner Revenue & Pipeline Own and exceed partner-sourced and partner-influenced revenue targets on a quarterly basis Proactively generate pipeline through Snowflake, Databricks, and GCP field AEs and PDMs — building the relationships that produce qualified, sourced opportunities Drive joint account mapping and target account activation against Prophecy's ICP: enterprises running Alteryx on Snowflake or Databricks Activate co-sell motions through marketplace programs (GCP Marketplace, Snowflake Partner Network, Databricks

Employee Applicant Privacy Notice Who we are: Shape a brighter financial future with us. Together with our members, we’re changing the way people think about and interact with personal finance. We’re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we’re at the forefront. We’re proud to come to work every day knowing that what we do has a direct impact on people’s lives, with our core values guiding us every step of the way. Join us to invest in yourself, your career, and the financial world. The Role: As a Technical Program Manager within the Enterprise Data Governance team, you will drive strategic execution across our core data governance processes. Your primary focus is to protect member privacy safeguarding personal information through secure handling, processing, and storage to ensure trust, enforce compliance, and mitigate data exposure risks. You will bridge the gap between corporate data governance policy and operational engineering, leading high-visibility technical programs that secure, classify, and institutionalize data controls across key data platforms. As a leader, you will partner with engineering, the CIO organization, Legal, Privacy Compliance, and broader stakeholders to shield enterprise data frameworks while accelerating feature delivery. What you’ll do: Own the end-to-end strategy, roadmap, and execution of complex, multi-platform data privacy and data protection initiatives, driving the Privacy Rights Management (PRM) program as a primary priority. Partner with engineering and platform teams to translate abstract data governance and privacy policies into actionable technical execution. Own the requirements lifecycle by authoring comprehensive PRDs, defining functional data controls, and ensuring engineering teams have the clear technical specifications needed

Location Details: Remote - Canada (BC or ON) At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​ This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings. This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands. Join our team GoDaddy is expanding its data and AI capabilities while strengthening the governance, security, privacy, and compliance foundations needed to support responsible growth. As data usage and AI adoption accelerate, we are building scalable governance and control frameworks that enable innovation while maintaining strong accountability, audit readiness, and regulatory compliance. As the Senior Technical Program Manager - Data, AI Governance and SOX Compliance , you will lead cross-functional programs that improve data governance, AI governance, access accountability, and SOX compliance across the business. Partnering with engineering, data, security, finance, legal, audit, and compliance teams, you will drive strategy, execution, and operating mechanisms that make governance and controls visible, scalable, and embedded into daily operations. This is a high-impact role for a program leader who thrives in ambiguous environments. They can influence various interest groups and are passionate about helping teams move faster. They focus on growing transparency, strengthening controls, and boosting confidence in managing data, AI, and compliance risks. What you'll get to do... Lead complex, cross-functional programs spanning data, AI, security, compliance, audit, and finance, driving initiatives from problem definition through rollout, adoption, and measurable business outcomes. Develop and manage program plans, governance

Data Engineer, Data Platform About the Role We are building out our Data Platform team at Sigma, with a relentless focus on developing data models that fuel trusted insights across the company. As a Data Platform Engineer, you will be responsible for the underlying data architecture across Snowflake and Databricks, as well as building and optimizing various ETL pipelines to fuel both internal and external (demo) use cases. Reporting to the VP of Data & Revenue Engineering, this is a high visibility role with the opportunity to work on greenfield projects. If you’re a data engineer with a builder mindset who wants to leverage a best-in-class stack, and genuinely is invested in Sigma’s mission, let’s chat! What You Will Be Doing Architect and manage our production data pipelines in Snowflake and how they are consumed in Sigma ( Tech we use : Fivetran, dagster, dlt, terraform, dbt, Snowflake, Sigma, Hightouch, Metaplane) Build foundational processes for scaling our demo asset data across various Cloud Data Warehouses Scale our terraform deployment across all of our Snowflake assets Continue to advance our data governance policies Work cross functionally to accomplish all of the above! You’ll work across Product, Engineering, GTM—with users of all skills and levels Qualifications We Need Strong knowledge and experience of working with APIs and building data pipelines from various systems into Cloud Data Platforms (e.g., Snowflake, Databricks) Strong communication and collaboration skills. You will primarily partner with the Analytics and Infrastructure Engineering teams internally at Sigma; your ability to work and collaborate closely with them will be integral to your success. Experience deploying data governance frameworks with a scalable and repeatable process Ability to thrive in ambiguous environments and get stuff done. We move fast and iterate quickly, and we want you to feel empowered to do exactly that 3+ years of relevant experience wor

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. As a Senior Software Engineer, Data on the Mapping team, you will collaborate with our world-class team of engineers, product managers, and scientists to grow and improve the quality of recommended routes and accuracy of our travel time estimations. You will lead the architecture and long-term technical direction of our offline experimentation tooling and route simulation services — the systems that let Lyft test routing changes safely before they reach production. You'll also build scalable data pipelines for experimentation, analytics, and machine learning models, along with the data governance and observability systems that keep them trustworthy. Your work will enable integration with partner teams and allow stakeholders across Engineering, Data Science, and Product to make data-informed decisions that directly impact Lyft’s growth and profitability. Our technology stack is based on the latest technologies such as AWS, Databricks, Kubernetes and Airflow. You will work with incredibly passionate and talented colleagues from software engineering, machine learning and data science on projects that directly impact millions of riders and drivers. Responsibilities Own core data pipelines end-to-end, building deep subject matter expertise in the systems you manage and defining/managing SLAs for pipelines, services, and datasets to ensure reliability at scale Serve as the technical owner and architectural lead for our offline experimentation platform and route simulation services, setting technical direction, evaluating trade-offs, and ensuring the systems scale with Lyft's routing and mapping ambitions Continuously evolve data models and schemas to meet business and engineering requirements Develop AI tools that support self-service management of data pipelines (ETL) and schema evolution, and perform han

About the Team DoorDash’s Internal Audit team provides independent assurance that the company’s risk management, governance, and internal control processes are operating effectively. We are a small team that is looking to expand and bring on motivated professionals. We don’t think of ourselves as a typical audit function - we are obsessively focused on risks to the organizations which reflects in the type of projects we support and execute. DoorDash is rapidly growing - we are expanding in multiple geos and launching new products. This exciting growth allows us to drive creative analysis, strategy, and solutions. Our focus areas include financial, operational, regulatory, security, IT, and more. About the Role We are seeking a Senior Director, IT Internal Audit to lead the strategy, execution and evolution of DoorDash’s global IT audit function. In this highly visible role, you will help shape the technology risk management practices across DoorDash - you will oversee a broad portfolio of audits, including IT SOX, cybersecurity, data governance, AI governance, and operational technology. You will report directly to the Chief Audit Executive and serve as a strategic advisor to DoorDash’s technology, security, and engineering leaders. You will bring deep technical audit expertise, exceptional leadership skills, and a passion for innovation to build and lead a world-class IT audit organization that scales with the business. This role demands someone who can balance strategy with execution (and isn’t afraid to roll up their sleeves) — a leader who can anticipate emerging technology risks, foster strong cross-functional partnerships, translate complex technical concepts into meaningful business insights, and be ready to operate at the lowest level of detail. You will partner with teams across Security, Platform Engineering, Data Engineering, Privacy Legal, AI, Product, and Compliance to strengthen our risk posture and drive a data-driven approach

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. We’re looking for a proactive, collaborative Manager of Internal Audit to help execute our internal audit program and support Lyft’s governance, risk management, and compliance efforts. This role will focus on both business and technology audits, helping identify and address key risks while delivering insights that enable informed decision-making. Reporting to the Director of Internal Audit, and based in our San Francisco HQ, you’ll work closely with stakeholders across the company to strengthen controls, improve processes, and drive continuous improvement. Responsibilities: Audit Execution & Risk-Based Planning Execute audit and advisory engagements spanning across both technology (e.g. cybersecurity, data governance, infrastructure, etc.) and business (e.g. operations, compliance, etc.) domains from end to end — including planning, fieldwork, testing, and reporting. Perform annual risk assessment over assigned risks to develop and refine the annual risk-based audit plan. Take a hands-on approach to audits, ensuring findings are data-driven, relevant, and aligned with business objectives. Use process improvement techniques (e.g. process mapping, root cause analysis, gap assessments) to identify opportunities for enhanced control design and operational efficiency. Perform risk assessments and identify areas for process improvement, control enhancement, or technology enablement. Ensure timely and effective follow-up on remediation of audit findings, coordinating with business owners to verify resolution. Collaborate with cross-functional teams — including Engineering, Security, Legal, Finance, and Compliance — to assess risks and test key controls. Stay current on evolving risks related to emerging technologies, regulatory changes, and internal initiatives. Enterprise Risk Management (ERM) Support

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. We’re looking for a proactive, collaborative Manager of Internal Audit to help execute our internal audit program and support Lyft’s governance, risk management, and compliance efforts. This role will focus on both business and technology audits, helping identify and address key risks while delivering insights that enable informed decision-making. Reporting to the Director of Internal Audit, and based in our San Francisco HQ, you’ll work closely with stakeholders across the company to strengthen controls, improve processes, and drive continuous improvement. Responsibilities: Audit Execution & Risk-Based Planning Execute audit and advisory engagements spanning across both technology (e.g. cybersecurity, data governance, infrastructure, etc.) and business (e.g. operations, compliance, etc.) domains from end to end — including planning, fieldwork, testing, and reporting. Perform annual risk assessment over assigned risks to develop and refine the annual risk-based audit plan. Take a hands-on approach to audits, ensuring findings are data-driven, relevant, and aligned with business objectives. Use process improvement techniques (e.g. process mapping, root cause analysis, gap assessments) to identify opportunities for enhanced control design and operational efficiency. Perform risk assessments and identify areas for process improvement, control enhancement, or technology enablement. Ensure timely and effective follow-up on remediation of audit findings, coordinating with business owners to verify resolution. Collaborate with cross-functional teams — including Engineering, Security, Legal, Finance, and Compliance — to assess risks and test key controls. Stay current on evolving risks related to emerging technologies, regulatory changes, and internal initiatives. Enterprise Risk Management (ERM) Support

About the Team The DoorDash Research Fellowship is a 3-month program (extendable to 6 months) looking for Summer and Fall 2026 cohorts, for researchers and engineers who want to work on the hardest applied ML and AI problems in local commerce. Fellows are given the resources, autonomy, and access to real-world operational data needed to pursue ambitious research directions — with the goal of producing work that influences both the field and how DoorDash operates at scale. This program is modeled on the best external research fellowships: fellows are treated as independent researchers, not as junior employees on a product team. You pick the problem (within a set of priority areas), you own the direction, and you publish or ship the outcome. You’re excited about this opportunity because you will receive… Dedicated compute allocation sized to the research agenda — GPU clusters for training and inference budgets for experimentation Full access to DoorDash's research infrastructure — our internal RL stack, training and evaluation pipelines, RL environments built on real operational systems, agent evaluation harnesses, and the tooling our own research teams use day-to-day. Fellows are first-class users, not sandboxed visitors. Access to DoorDash operational data — real-world datasets spanning logistics, merchant operations, consumer behavior, and marketplace dynamics, under appropriate data governance Research mentorship from senior researchers and engineering leaders at DoorDash, plus a named research sponsor for each fellow who meets with you weekly and is accountable for unblocking your work Speaker series featuring leading researchers and practitioners from academia and industry — faculty from top ML programs, research leads from frontier AI labs, and senior operators from across tech. Fellows get dedicated 1:1 time with speakers when possible. A cohort of fellows working alongside you — a small, tight-knit group of researchers tackling different problems but sharing

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. About the role The App Runtime team is building a platform that lets every Snowflake user go from an idea to a live, deployed web application (Node.js first) in minutes. We own the end-to-end experience of building and running apps, from Cortex AI-assisted development to deployment in a secure, scalable infrastructure. Apps built on the platform inherit Snowflake's security, governance, lineage, and access controls by default. See Deploy Faster with Snowflake Apps . As a Staff/Principal Engineer, you will shape the product and its architecture. It’s a high leverage role - you will lead a team to scale and harden an early-stage, public-preview product. Your decisions will have a long-lasting impact on the future of Snowflake as an app platform. This role requires a unique combination of deep hands-on expertise in scalability, performance and security, great product instincts, customer obsession and the organizational influence to drive cross-team programs. Responsibilities Own the roadmap and technical decisions to evolve the public-preview platform into a production-grade one, adding features like horizontal scaling, cost efficiency via suspend/resume, support for stacks beyond Node.js, and stronger access and data-governance controls Stay deeply hands-on by authoring specs

This position is based in Vancouver, BC , within Diligent’s Technical Center of Excellence. We are currently hiring candidates who are based in or able to work from Vancouver . Software Engineer — Platform AI Service Levels: Software Engineer II Senior Software Engineer Staff Software Engineer Location: Vancouver Position Overview As a Software Engineer on Diligent's Platform AI team, you'll help design, build, and operate the core services that power AI-driven capabilities across Diligent's global product suite. You'll build secure, scalable, serverless services on AWS that translate AI research and models into commercial-quality, production-ready solutions — enabling customers to derive insights from their governance data. You'll work closely with AI researchers, product managers, and other engineering teams, owning your services end-to-end: architecture, implementation, deployment, and monitoring. The team operates with a strong AI-augmented engineering culture — using AI tools to accelerate coding, testing, debugging, and delivery — while applying sound judgment about when and how to apply them. Key Responsibilities Design and implement secure, scalable, fault-tolerant, high-performing solutions using AWS serverless technology — event-driven, highly observable, and built with infrastructure as code. Collaborate with AI researchers/engineers to translate AI and LLM capabilities into robust, production-grade services, and help other teams integrate them. Build and maintain the pipelines needed to deploy, monitor, and manage AI services at scale — observable, resilient, and cost-effective. Use AI-powered development tools (code assistants, test generation, architecture exploration) responsibly to accelerate delivery and improve quality, always validating outputs. Participate in architecture discussions and design reviews, and contribute to product design by understanding customer problems — especially where AI can offer a breakthrough solution. Work in