Data Governance Senior Jobs

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. Snowflake is about empowering enterprises to achieve their full potential with Data & AI. With a culture that's all in on impact, innovation, and collaboration, Snowflake is the sweet spot for building big, moving fast, and taking technology and careers to the next level. We're hiring for a Senior Director of Analytics Engineering to join our Data, Analytics, and AI organization (DAA), reporting directly to the Chief Data & Analytics Officer. You will lead a team of 20+ Analytics Engineers that build and operate the pipelines behind Snowflake's revenue, bookings, people analytics, and go-to-market reporting within our governed data platform. This role has an in-office requirement — you must be able to work out of our Menlo Park office a minimum of 3 days a week. In This Role You Will Lead and grow the Analytics Engineering organization: Manage through your direct reports (team leads/managers), setting priorities and technical strategy across the team. Drive Snowflake’s internal data transformation: Lead your teams' ongoing work to create an AI ready data foundation, with an emphasis on documentation, contracts, context, and governance. Own Snowflake’s internal analytics agents: Build, improve, and maintain general purpose analytics agents - and underlying context an

WPP is the trusted growth partner for the world’s leading brands. We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth. We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise. Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow. For more information, visit WPP.com. Why we're hiring: We are seeking a highly skilled and experienced Senior Data Engineer to join our growing data team. In this critical role, you will be instrumental in designing, building, and optimizing our scalable data lakehouse platform using Google BigQuery or Databricks. You will be a key player in developing robust data pipelines that ingest data from various sources, including Google Analytics 4 (GA4), and transform it into reliable, analysis-ready datasets within the lakehouse environment. This role requires deep expertise in modern lakehouse platforms – Google BigQuery and/or Databricks – together with strong skills in SQL, Python, and Apache Spark (PySpark), along with strong hands-on experience across Azure, AWS, and GCP cloud environments, as our data ecosystem spans multiple cloud platforms. You will be responsible for the entire data lifecycle within the lakehouse, from ingestion and transformation to governance and optimization, ensuring data quality and performance. You should be adept at analyzing performance bottlenecks in Spark jobs and BigQuery workloads, providing enhancement re

Senior Data Migration Specialist About the Project We are looking for an experienced Senior Data Migration Specialist to provide expertise on a large-scale transformation programme within the financial services sector. This opportunity is suited to a senior migration specialist who combines strong technical knowledge with experience coordinating complex migration activities across business and technology teams. The engagement focuses on migrating data from a legacy SaaS platform to a new strategic solution. The programme is currently shaping its migration approach and entering a critical phase of planning, reconciliation design, and cutover preparation. Scope of services: As a Senior Data Migration Specialist, you will: Coordinate the development and delivery of the end-to-end data migration strategy. Define migration approaches, data quality standards, validation criteria, and reconciliation processes. Coordinate the design and implementation of qualitative and financial reconciliation tooling. Collaborate with business stakeholders, solution architects, engineering teams, testing teams, and third-party vendors to ensure successful migration outcomes. Facilitate migration planning activities, including migration waves, cutover planning, rollback scenarios, and readiness assessments. Identify migration risks, dependencies, assumptions, and issues throughout the programme lifecycle. Communicate delivery progress, key risks, and dependencies to programme stakeholders. Contribute to the continuous improvement of migration methodologies, governance practices, and delivery standards. Required Experience Proven experience leading enterprise-scale data migration initiatives within financial services or another highly regulated industry. Strong technical knowledge of: data migration methodologies, ETL processes, data quality management, reconciliation approaches, migration tooling and validation techniques. Experience working with SaaS platforms and complex system mi

Drata is building the trust layer between great companies - automating compliance, managing risk, and helping organizations prove trust continuously as they scale. We're Dratanauts: a global crew of 600+ professionals united by a culture that rewards integrity, ownership, and raising the bar, no matter where in the world we're working from. Why Join the Drata Team? At Drata, you're not maintaining legacy compliance software - you're building the agentic AI platform defining what trust looks like for the next generation of companies. Here's what makes the work itself worth showing up for: Problems without a playbook: You'll work at the edge of AI and security, building agentic governance, continuous compliance, and real-time trust verification to solve problems that don't have an established answer yet. You're writing it as you go. Real ownership, not just process: Our values center on owning outcomes and raising the bar, not checking boxes. You're expected to have opinions and back them. A seat at the table: Your perspective is unique and valued. Open debate and diverse viewpoints are built into how decisions actually get made here, at every level. Growth at rocketship speed: Drata is scaling fast, which means scope grows fast too. High performers get more ownership, visibility, and experience. A crew, not just coworkers: Dratanauts consistently describe a "come as you are" culture with sharp, curious people—the kind of team that makes hard problems genuinely fun to solve. See what they say here and follow us on LinkedIn for company news, employee stories, and career updates. Job Summary: Drata is looking for a Senior Data Engineer! This person will be a key member of the growing data team, supporting one of the fastest growing B2B SaaS startups to achieve unicorn status. At Drata, we’re on a mission to help build trust across the internet! Data accuracy is an essential cornerstone of our mission. We are looking for a senior data engineer that can help us strategize

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. Snowflake Horizon Catalog is the context and governance layer of the Snowflake AI Data Cloud. AI is fundamentally transforming how enterprises monitor and trust their data: instead of manually configuring thresholds and triaging failures, AI-powered anomaly detection fires on freshness and volume deviations automatically, agentic root cause analysis traces quality failures back to their upstream source in minutes, and intelligent lineage surfaces the blast radius of any schema change before it reaches a dashboard. Snowflake's native Data Observability capabilities — Data Metric Functions, graphical column-level lineage, anomaly detection, and AI-powered root cause analysis — are the foundation of this next-generation trust layer. We are seeking a Senior Product Manager to own the Data Observability product area, spanning Data Quality, End-to-end Lineage, and Root Cause Analysis. You will define the strategy for how Snowflake competes and wins against best-in-class observability platforms, drive the AI-first transformation of how enterprises detect and resolve data quality failures, and lead a high-performing cross-functional team to deliver capabilities that make enterprise data pipelines self-healing and self-explaining at scale. AS A SENIOR PRODUCT MANAGER – DATA OBSERVAB

The Data Engineering team’s mission is to ensure high-quality data to enable data-informed decision-making across Asana. You will build data artifacts that are leveraged by Product and Business Data Science teams to optimize our user adoption, growth, and experience. In this role, you will partner with the Infrastructure team to build a self-service analytics platform for the company. This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday; most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements. What you’ll achieve Design, implement, and scale end-to-end data products that support growing data processing and analytical needs Transform raw data into actionable insights to drive product strategy and power in-depth analyses and reporting Leverage AI to build self-serve tools and accelerate Data/GTM workflows Partner with data scientists, domain experts, and engineering teams to develop a roadmap that aligns with our business goals Implement systems that guarantee data quality, governance, and availability About you 5+ years of experience in Data Engineering or Software Engineering Experience in data modeling and building scalable data pipelines involving complex transformations Proficiency in data processing and storage technologies like Databricks, AWS/S3, Python/Scala/Java, SQL, Spark, and Airflow Proactive and innovative in identifying and addressing performance bottlenecks in existing workflows Motivated to work closely with cross-functional partners to evolve our analytical data model Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making At Asana, we're com

Senior Data Scientist Location: London (Hybrid) | Practice Area: Data & Analytics | Type: Permanent Shape intelligent solutions. Lead with insight. Drive data innovation. The Role We are looking for a Senior Data Scientist to join Capco’s growing UK Data Practice. You will play a leading role in designing and implementing cutting-edge data science solutions across financial services. This is an opportunity to build intelligent systems that drive commercial and customer outcomes while mentoring others and collaborating in a dynamic, multi-disciplinary environment. You'll also embrace AI-enabled ways of working, using approved AI tools where appropriate to enhance delivery while applying sound professional judgement. What You’ll Do Lead the end-to-end delivery of data science solutions including PoCs, MVPs and production deployments. Develop and prototype ML models to solve complex business challenges using modern techniques and tooling. Collaborate closely with engineers, domain experts, and business teams to translate requirements into deliverables, using approved AI tools where appropriate to improve efficiency and accelerate insight. Guide and coach data science pods, supporting skill development and solution design. Act as a subject matter expert on ML architecture, model calibration, and productionisation, promoting responsible AI practices and scalable model governance where applicable. What We’re Looking For Hands-on experience building and deploying data science solutions in Python and related ML libraries. Strong background in applied machine learning, model development, and data engineering, with an appreciation of responsible AI principles. Experience with cloud environments (Azure, AWS, GCP) and tools such as Spark, Hive, and Redshift. Demonstrated ability to lead cross-functional teams and mentor junior practitioners. Ability to communicate complex technical concepts clearly to non-technical audiences and apply AI-enabled approaches to deliver practi

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build storage technologies, client libraries, and filesystem frameworks that help AI workloads access data across object stores, file systems, and hybrid cloud infrastructure. Develop high-performance storage paths for training and inference workflows, including data loading, checkpointing, caching, POSIX-style access, and object-store integration. Build observability systems that diagnose storage bottlenecks, attribute GPU idle time to I/O behavior, and expose actionable telemetry through production monitoring stacks. Improve performance, scalability, and reliability of storage systems serving massive datasets, deep directory trees, and high-concurrency AI workloads. Work closely with internal AI teams, platform teams, SRE, and operations to validate storage behavior against real workloads and production environments. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, performance, and verification. What we need to see: BS in Computer Science, Information Sys

The NVIDIA DGXC Data Services team builds cloud-native systems, frameworks, and services for managing data across hybrid and multi-cloud infrastructure. We are building the next-generation data and storage infrastructure to solve some of the hardest problems in AI: storage, access, ingestion, governance, observability, and data management for exabyte-scale, high-performance GPU-based training and inference jobs. Our work gives NVIDIA teams the foundational capabilities they need to build, train, deploy, and operate AI products at scale without reinventing critical data infrastructure for every workload. What you will be doing: Build cloud-native data and storage services for hybrid and multi-cloud infrastructure, including dataset discovery, ingestion, governance, checkpointing, observability, and low-latency access. Develop scalable cloud-native services and APIs that support exabyte-scale, high-performance GPU training and inference workflows. Work closely with product managers, internal AI teams, platform teams, and partner engineering teams to understand requirements and turn them into reliable production systems. Collaborate with SRE, operations, and support teams to improve service reliability, performance, observability, on-call readiness, and operational scale. Use modern software engineering practices, including AI-assisted and agentic development workflows, while maintaining high standards for design, testing, security, and verification. What we need to see: BS in Computer Science, Information Systems, Computer Engineering, or equivalent experience, with 5+ years of software engineering experience. Strong foundation in algorithms, data structures, distributed systems, and practi

Senior Data Engineer, Proprietary Research London A Career with Point72's Market Intelligence team On our proprietary research team—Market Intelligence— you will uncover insights about markets and the broader economy through deep compliant fundamental research and applying data science and engineering techniques to alternative data sets. In partnership with our investment professionals and Compliance team, our team of analysts, data scientists and engineers work together to produce compliant research and build tools that inform our firm’s investments. We look for other bright, motivated, and collaborative people to join our team and grow with us—a majority of the leaders in our group were promoted from within. WHAT YOU'LL DO Work closely with investment professionals, researchers, and data scientists to design, build, and launch robust end-to-end business solutions including data pipelines, products and tools. Design and develop big data processing pipelines including but not limited to ingestion, transformation, trends creation to deliver AI-ready data assets & products. Develop reusable software components, libraries, and APIs that enable rapid experimentation and production deployment Implement data quality, lineage, and governance controls to ensure datasets are reliable, auditable, and compliant with compliance policies Build scalable AI-native cloud-based infrastructure using distributed systems techniques, to deliver efficient data-driven business solutions Optimize performance, cost, and reliability of software systems through benchmarking and iterative improvements WHAT’S REQUIRED 5+ years of experience in Data Engineering, Software Engineering or related field 2+ years of strong experience in Python development Experience with system design and leading multi-person development efforts Experience with distributed data processing frameworks like Spark Experience with building scalable APIs, and software applications w/ focus on backend infra

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. POSITION SUMMARY CVS Health is seeking a highly skilled Senior Data Engineer, Observability Engineering to join the Enterprise Observability Platform organization and help advance the next generation of observability, infrastructure, and security data capabilities. The Senior Data Engineer, Observability Engineering will play a critical role in designing, building, and operating scalable data pipelines and data products that power enterprise observability, operational intelligence, and security analytics across the organization. The Senior Data Engineer, Observability Engineering is a senior individual contributor responsible for developing and optimizing Databricks-based data engineering solutions that ingest, transform, govern, and deliver high-volume telemetry, infrastructure, application, and security data. This role combines deep hands-on technical execution with ownership of engineering excellence, operational reliability, performance optimization, and data platform best practices. Working closely with Observability Engineering, Security Engineering, Infrastructure Engineering, and Data Platform teams, the Senior Data Engineer, Observability Engineering will contribute to the evolution of the enterprise observability lakehouse by building resilient ingestion frameworks, establishing data quality standards, enhancing governance controls, and driving efficient, scalable data processing patter

DataHub is an AI & Data Context Platform adopted by over 3,000 enterprises, including Apple, CVS Health, Netflix, and Visa. Innovated jointly with a thriving open-source community of 13,000+ members, DataHub's metadata graph provides in-depth context of AI and data assets with best-in-class scalability and extensibility. The company's enterprise SaaS offering, DataHub Cloud, delivers a fully managed solution with AI-powered discovery, observability, and governance capabilities. Organizations rely on DataHub solutions to accelerate time-to-value from their data investments, ensure AI system reliability, and implement unified governance, enabling AI & data to work together and bring order to data chaos. Senior Product Manager, Observability & Data Quality As a Senior Product Manager, for Observability & Data Quality, at DataHub, you will work cross-functionally to help guide products from ideation to launch by connecting the technical needs of users and the business needs of our company. You will help define the vision, goals, and strategy we pursue in concert with engineers, designers, sales, and partners that move the practice of analytics engineering forward. We are pursuing an ambitious AI strategy, focused on building a unified Context Platform that solves context fragmentation, maintenance, validation, and accessibility challenges. In this role, you can expect to: Define the vision, goals, strategy, tactics, and roadmap for our suite of products Study, research, and understand the data ecosystem, with a specific focus on user requirements, market potential, and competitive landscape Serve as the accountable owner for delivering measurable business and customer outcomes; working closely with designers to create intuitive, elegant user experiences for technical and non-technical personas Create tight feedback loops with customers who are depending on DataHub to run their data environments so that the product evolves toward the needs of these stakeh

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Senior Data Analyst - Field Analytics As part of Okta’s Go-To-Market Strategy & Operations group, the Field Analytics team drives insight and scale within the global field organization. We serve as the core engine for the analytics and strategic analysis that enable our leaders to make data-driven decisions that determine the trajectory of Okta’s growth. You will be responsible for building high-impact technical assets, ranging from executive Tableau dashboards to standardized Snowflake datasets, while staying at the forefront of AI-driven analytics workflows. You will partner with US-based leadership and local team members to ensure our reporting framework is scalable, accurate, and deeply aligned with Okta’s global GTM strategy. Job Duties & Responsibilities: Analytics Delivery: Design, build, and maintain high-visibility Tableau dashboards and reporting assets that provide actionable insights to business partners across the global organization Data Set Engineering: Build and optimize production-grade data sets in Snowflake, ensuring that all field data (Pipeline, Bookings, Productivity) is clean, structured, and easily accessible for self-service analysis. Documentation & Governance: Take ownership of the technical documentation for all GTM reporting assets, ensuring data lineage, metric definitions, and logic are clearly defined and accessible. AI Implementation: Champion the use of Generative AI tools to accelerate the analytics lifec

About Eve Eve is redefining legal technology for plaintiff law firms, and we're building the team that will take us there. We help firms handle more cases, recover more for clients, and grow with AI that works across every stage of a case, from intake through resolution. The next generation of great plaintiff firms will be AI-Native, and Eve is how they get there. But what makes Eve different isn't just the product. It's how we build it. If you're someone who takes ownership, stays curious, and wants to build AI that's already changing how law is practiced, this is where you belong. Product-market fit: Eve is trusted by over 1000+ law firms, and we’re growing fast. Backed by top investors: We’ve raised over $160M from world-class partners including Spark Capital, Andreessen Horowitz(A16z), Menlo Ventures, and Lightspeed. Built by a world-class team: Engineers, designers, and operators from places like Scale, Meta, Airbnb, Cruise, Square, Rubrik, and Lyft are building Eve from the ground up. AI-Native from day one: We’re on the bleeding edge of AI, collaborating directly with teams at OpenAI and Anthropic to build best-in-class AI workflows tailored for legal work. Explosive growth: We are growing 2X revenue Quarter over Quarter. The Role Eve is doubling revenue quarter over quarter, and the platform is being built to keep pace. A medallion architecture is in place on a Terraform-managed Snowflake footprint. Most of what goes on top is still ahead: ingestion and orchestration built for the volume coming, reliability practice, the access and governance model, and the standards every contributor works inside. The data spans product usage, case and firm data, and every go-to-market system Eve runs on. Analytics engineers and business analysts build models and reporting on top of it, AI agents query it directly, and leadership makes calls on it weekly. When a pipeline fails quietly, all three inherit the mistake. You'll own the pipelines carrying all of that,

Work Flexibility: Remote As a Senior Lead, Data Engineering, you will serve as a technical leader who helps shape the future of enterprise data solutions. In this role, you will drive complex data initiatives, influence technical strategy, and partner with teams across the organization to build scalable, high-impact data products. This is an opportunity to solve challenging business problems while mentoring fellow engineers and elevating data engineering best practices. What You Will Do Lead the architecture, development, and modernization of scalable enterprise data platforms that support global procurement analytics and business transformation. Define and help execute a multi-year data engineering strategy focused on platform scalability, reliability, automation, technical debt reduction, and long-term maintainability. Design, build, and optimize Azure-based data solutions using technologies such as Databricks, Delta Lake, Azure Data Factory, Azure DevOps, CI/CD pipelines, and infrastructure automation. Integrate and harmonize data across multiple ERP systems by standardizing supplier, purchasing, and master data into common enterprise data models. Partner with procurement analysts, architects, engineers, and business stakeholders to translate complex business needs into reusable, scalable data products and engineering solutions. Establish engineering standards, conduct architecture reviews, improve documentation, and mentor engineers to raise the overall technical capability of the team. Identify and implement AI-enabled approaches that accelerate development, improve data quality, automate documentation, support testing, and enhance analyst productivity. Evaluate and recommend tools, frameworks, patterns, and platform investments that improve performance, reliability, security, governance, and operational ef