Data Governance Analyst Banking in United States

Demand Generation Data Analyst — Nashville, Tennessee, United States. Apply via Workday.

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Washington D.C., London and Amsterdam. Making data driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide tooling and guidance to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. Engineers on Data Infrastructure are domain experts in Data Warehouse, Data Lakehouse, Spark, Workflow Orchestration, and Streaming technologies. We scale our existing data pipelines in a performant and cost efficient way while creating the necessary abstractions to make developing on top of this platform extremely simple for other engineers at Plaid. Responsibilities Contribute towards the long-term technical roadmap for data-driven and machine learning iteration at Plaid Leading key data infrastructure projects such as improving ML development golden paths, implementing offline streaming solutions for data freshness, building net new ETL pipeline infrastructure, and evolving data warehouse or data lakehouse capabilities. Working with stakeholders in other teams and functions to define technical roadmaps for key backe

What you’ll do Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews. Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet. What we’re looking for Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability. Experience shipping production systems that handle large data volumes and failure-prone networks. Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments. Useful experience Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability. Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails. Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks. Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.

About Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. Help Win New Business The Opportunity: We are scaling our dedicated Data Center practice, and we are looking for the person who will lead it. This is a founding commercial role. You will start as a team of one, owning the full sales motion end-to-end, and you will build the team around you as the practice grows. You will define how Flexport goes to market with hyperscalers, hardware OEMs, and the broader ecosystem. You will set the playbook, win the first marquee accounts, and hire the people who scale what you build. Reporting directly to the Regional General Manager, you will operate with a high degree of autonomy and direct access to executive leadership. This role features a 50/50 compensation model (Base + Uncapped bonus, with accelerators), with OTEs of $350k+, designed for strong leaders who take bets on themselves. Why This Role Is Different: The data center logistics market is not a standard freight problem. A single AI compute rack can cost more than $1 million and weigh up to 4,000 pounds. Racks contain Class 9 dangerous goods (lithium-ion batteries) and liquid cooling systems requiring specialized handling. Construction sequencing failures delayed 57% o

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. At Roblox, we strive to connect a billion people with optimism and civility, and the Safety organization’s mission is to become the leader in civil immersive online communities. We systematically detect, remove, and prevent problematic accounts, content and behavior, and we make Roblox accounts secure and free from compromise. We cover a broad area of the tech spectrum, including machine learning, classifiers for 3D models, experimentation, automation, detection workflows, and AI-powered text filters. Aligned and partnering with product teams, we use this tool-belt to discover new opportunities, influence and shape the product roadmap and prioritization, build safety products, and measure the impact on our community of users and developers. In doing so, we keep Roblox safe, civil, and inclusive, and we foster positive relationships between people around the world. WHY Safety Data Infrastructure To pro-actively find bad actors and protect good users, Roblox needs to ingest enormous amounts of data and make it usable both to our automated detection systems and for human moderators and customer support agents doing investigations. The Safety Data Infrastructure team is addressing these needs w

Datadog's Finance team collaborates with teams across the organization, providing commercial, operational and analytical support to ensure that Datadog's business continues to scale rapidly and efficiently. The Financial Planning & Analysis (FP&A) team analyzes company financial data (revenue, customers, headcount, expenses, etc.) in order to support the business’ growth and success. As an analyst supporting the team, you will play a key role in delivering insights through the management of essential data infrastructure, including our financial planning tool, Pigment. Your role will be highly cross-functional, leveraging systems and data to unlock analytical capabilities for both FP&A and business leaders. Your role is critical in synthesizing information from across the organization to foster operational alignment and support informed strategic decisions. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Own the team’s forecasting and reporting software, Pigment, supporting data-driven insights through the development of dashboards and KPIs, both for standard FP&A reports and ad hoc projects Work cross-functionally with FP&A leaders to improve existing datasets and models Ensure data and system best practices in processes across the organization, including during planning and reporting cycles Represent FP&A in the data & analytics community, collaborating with analytics partners across the organization to democratize data and share insights Work on strategic projects and initiatives for senior management, assessing various business opportunities and proposing solutions Support Datadog’s data-based decision making and continued efficient growth Who You Are: 2+ years of professional experience in FP&A, Data Analy

At Datadog, we’re on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at high scale, enabling seamless collaboration and problem-solving among Dev, Ops, and Security teams globally for tens of thousands of companies. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way. The Observability Data Platform (ODP) is the backbone of everything Datadog delivers – powering how data is ingested, stored, routed, and surfaced across every product at planet scale. As a Senior Product Manager for ODP, you will work with world-class engineers and cross-functional partners to shape how the platform is deployed, controlled, and operated. You will define product direction across the control plane and data layer, translate complex infrastructure trade-offs into clear roadmap decisions, and help customers get the most from their observability investment – regardless of architecture, topology, or scale. At Datadog, we place value in our office culture – the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You Will Do: Develop a deep understanding of the Observability Data Platform customers – platform engineers, SREs, and product managers that own the product verticals – their infrastructure challenges, deployment topologies, and cost-to-serve trade-offs. Define product direction across multiple ODP surfaces, including the control plane and data layer, by articulating clear problem statements and desired outcomes, and partnering with engineering on technical approach and sequencing Lead conversations with design partners and strategic customers to understand real-world platform pain points, validate product assumptions, and guide solutions from early prototypes through General Availability Develop a co

About the Team This team builds and operates the systems that enable OpenAI researchers to run reliable, scalable, and efficient research workflows. The team sits close to research and works across infrastructure, systems, and automation to make sure researchers have the tools and environments they need to move quickly. The work spans software engineering, infrastructure, systems administration, cluster operations, and reliability engineering. As OpenAI’s infrastructure evolves from bespoke bare-metal systems toward more standard, scalable platforms, the team needs engineers who can understand how systems work end-to-end and build the right abstractions without reinventing the wheel. About the Role As a Software Engineer on this team, you will build and operate the infrastructure that supports frontier research and critical research-facing systems. You will work on systems that sit close to the metal, but the role is not limited to classic operations or sysadmin work. We are looking for someone who can reason about networking, bootstrapping, Kubernetes, scalability, automation, and reliability - while also writing software to make these systems better over time. This role is a strong fit for an independent, high-ownership engineer who enjoys reliability-heavy infrastructure work but still wants to build. You do not need to come in as a kernel expert or highly algorithmic optimization engineer, but you should be deeply curious about infrastructure, comfortable debugging complex systems, and excited to support researchers doing novel work. We expect you to: Build and operate reliable infrastructure for research workloads and research-facing services. Support and improve systems across data infrastructure, processing, crawl and ingest, caching, search, observability, and clusterwide services. Improve cluster bootstrapping, provisioning, automation, and deployment workflows. Debug issues across networking, compute, storage, orchestration, and service reliability layers.

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Software Engineer to join our Data Acquisition team. Responsibilities: Own and lead engineering projects in the area of data acquisition including web crawling, data ingestion, and search. Collaborate with other sub-teams, such as Data Processing, Architecture, and Scaling, to ensure smooth data flow and system operability. Work closely with the legal team to handle any compliance or data privacy-related matters. Develop and deploy highly scalable distributed systems capable of handling petabytes of data. Architect and implement algorithms for data indexing and search capabilities. Build and maintain backend services for data storage, including work with key-value databases and synchronization. Deploy solutions in a Kubernetes Infrastructure-as-Code environment and perform routine system checks. Conduct and analyze experiments on data to provide insights into system performance. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in software development. Experience with large web crawlers a plus Strong expertise in large stateful distributed systems and data processing. Proficiency in Kubernetes, and Infrastructure-as-Code concepts. Willingness and enthusiasm for trying new approaches and technologies. Ability to handle multiple tasks and adapt to changing priorities. Strong communication skills, both written and verbal. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

About Team Our Robotics team is focused on unlocking general-purpose robotics and advancing toward AGI-level intelligence in dynamic, real-world environments. Working across the full model and systems stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the physical constraints of real-world systems to improve people’s lives. About Role We are looking for an Operations Program Manager - Robotics Data Acquisition to own the day-to-day operating rhythm in our data collection facilities. You will work closely with operators, technicians, program managers, and engineers to keep rigs ready, campaigns moving, issues resolved, and performance improving. This is a hands-on operations role that requires you to be comfortable spending time on the floor, working through ambiguity, and using data to make the operation more reliable and efficient. This role is based in San Francisco, CA and requires in-person presence 5 days a week. In this role you will: Coordinate daily operations readiness across workstations, operators, materials. Track core operating metrics including utilization, cycle time, throughput, downtime, operator productivity, and data quality. Identify bottlenecks through workflow analysis, time studies, and capacity modeling, then drive practical fixes. Execute the rollout of new hardware, sensors, tools, and process changes with Engineering, Operations, Facilities, Supply Chain, and Safety. Identify equipment readiness issues and coordinate with technical support to keep workstations, and test equipment calibrated, configured, maintained, and ready for rollouts and evaluations. Lead root cause analysis for recurring operational issues and follow through on corrective actions. Provide operation input to create and maintain SOPs, work instructions, training materials, and process controls. Identify and flag resource constraints and manage issue escala

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Full-Stack Engineer to join our Data Acquisition team to build and optimize the interfaces and tools that power our data infrastructure. Responsibilities: Develop and maintain full-stack applications that support data acquisition, including internal tools and dashboards. Collaborate closely with cross-functional teams, including Data Processing, Architecture, and Scaling, to ensure seamless data ingestion and workflow management. Design and implement APIs to facilitate data interactions between internal services and external data sources. Enhance user experience by developing intuitive web-based interfaces for managing and monitoring data pipelines. Optimize backend services for performance, scalability, and security in a distributed computing environment. Work with legal and compliance teams to ensure our data acquisition processes adhere to privacy regulations and best practices. Deploy and maintain infrastructure using Kubernetes and Infrastructure-as-Code (IaC) methodologies. Analyze system performance, conduct experiments, and improve data workflows to maximize efficiency. Qualifications: BS/MS/PhD in Computer Science or a related field. 4+ years of industry experience in full-stack development. Proficiency in frontend frameworks (React, Vue, or similar) and backend technologies such as Python, Node.js, or Go. Strong expertise in RESTful APIs, GraphQL, and database design (SQL and NoSQL). Experience building data-intensive applications that handle large-scale datasets. Familiarity with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker). Prior experience with web crawling and large-scale data processing is a

About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We're looking to advance how OpenAI builds and understands pretraining data at scale. You'll treat data quality and curation as core research problems: developing new methods to select, combine, and transform data; creating datasets that improve model capabilities; and designing rigorous experiments to understand how data choices and interventions affect model learning and downstream behavior. You'll work closely with frontier models and web-scale data to build evidence for which approaches work and why, then translate successful research into scalable data processing pipelines We Expect You To Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. Own and drive a research agenda, from choosing the right problems to carrying long-running work through to impact. Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. Experience building high-performance deep learning or large-scale data processing systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer

About the Team The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. We support critical domains across identity, access, infrastructure security, enterprise systems, and internal productivity. As OpenAI grows, audit readiness and control assurance increasingly depend on reliable data: accurate system inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. Our goal is to move beyond manual evidence collection and build scalable data products, automated validation, and continuous control monitoring that make security and IT controls measurable, repeatable, and defensible. About the Role We are looking for an IT Controls Data Engineer to build the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. In this role, you will design and maintain the pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to turn complex system behavior into reliable control data products. This is a technical builder role. The ideal candidate is strong in data engineering and analytics engineering, comfortable working with enterprise and security system data, and able to explain data lineage, source-system behavior, and control logic clearly to technical and audit stakeholders. You’ll be responsible for Building reliable data pipelines, models, and datasets for IT controls, including access, identity, configuration, change, ticketing, exception, and evidence data. Creating data quality, lineage, reconciliation, and completeness checks that make control data defensible for SOX and other audit use cases. Designing automated evidence generation workflows that produce compl

About the team Online Data builds and operates Habitat, the single product surface of Online Data and the system of record for OpenAI’s online user data. As OpenAI’s scale and product requirements evolve, Habitat is becoming a full-stack, one-size-fits-most database platform with end-to-end ownership of: Provisioning and developer experience APIs and guardrails Scaling, performance, and reliability Data movement, caching, routing, and placement Privacy enforcement and access control Change Data Capture (CDC) as a first-class primitive The foundation for future storage backends You’ll work on the core online database platform behind OpenAI’s products, building and operating Habitat services that handle high-QPS, latency-sensitive workloads across regions. You’ll partner closely with internal platform and product teams to ship safe, reliable systems, then push them to be faster and more cost-efficient through better caching, routing, observability, and operational tooling. This is a critical role for engineers who like owning hard distributed-systems problems end to end and sweating the details from p99 latency to production operations at massive scale. In this role, you will Design and build core abstractions spanning storage, caching, routing, CDC, and privacy enforcement Own a major surface area end to end, from product and API design to operational excellence Improve latency, correctness, and cost efficiency for real production workloads at massive scale Build strong instrumentation, debugging workflows, and developer-first tooling Collaborate closely with internal product and infrastructure teams to understand requirements and ship pragmatic solutions Participate in an on-call rotation and raise the bar on reliability while aggressively improving performance and usability You might thrive in this role if you have A strong track record building and operating high-scale backend or data-intensive distributed systems in production Excellent systems judgment and the a