Data Analytics Engineer Jobs

We are looking for a Senior Software Engineer to help us take REDAPL, our Referential Data Platform, to the next level. REDAPL is Datadog's main platform for tracking our customers' infrastructure resources and relationships. The platform enables products where customers can understand, keep track of, and gain insights into their infrastructure related to performance, cost, security, and more. Many Datadog products use REDAPL today such Cloud Security Posture Management, Resource Catalog, Cloud Cost Management, and Service Catalog and others - REDAPL ingests more than 4.5mil updates/second. As a Senior Engineer, you will drive, lead and collaborate on projects both inside and outside the platform. You can expect to contribute to key technical decisions relating to our data ingestion, processing, and query pipelines. 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: Build a query engine that supports efficient relationship traversals for our most demanding workloads. Contribute to design and drive high-priority, high-visibility projects to increase the platform's value, resilience, and scalability across multiple teams. Lead and guide other engineers through architectural platform decisions Identify potential system risks and trends in reliability and design solutions to address them Provide input on prioritizing engineering-led initiatives in short- and long-term planning and roadmaps Collaborate with internal product teams to understand their requirements and how we plan for their product growth as they integrate and depend on REDAPL Who You Are: You have a BS/MS/PhD in a Computer Science, Engineering or related scientific field or equivalent experience You have worked extensively with multiple types of data stores You have contributed to in

P- 1536 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Partner Ecosystem team’s mission at Databricks is to enrich and win customer workloads through seamless integrations with strategic partners, while also widening the partner ecosystem to include new partners and data applications. This team enables seamless connectivity between Databricks and a vast range of partner applications through SQLDrivers. This vital data integration work powers the majority of the company’s Data Warehousing revenue by allowing customers to effortlessly connect their applications to Databricks SQL. In addition to that, through products like Databricks Partner Connect, we are simplifying the discovery and integration process, allowing you to seamlessly incorporate your preferred tools directly within the Databricks platform. We are seeking an experienced Staff / Sr Staff Engineer to join our Partner Ecosystem team. In this role, you will design, develop, and maintain SQL drivers that power the majority of the data warehousing traffic and critical infrastructure components that power our partner integrations. You'll focus on optimizing SQLDrivers for performance, improved reliability and telemetry to offer seamless connectivity to our partners and enterprise customers, while also maintaining open source repositories and actively engaging with the developer community. You will collaborate wi

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps,

Scale Labs, Research Scientist — Safety Post Training As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Safety Post-Training you will develop and apply post-training methods and interpretability techniques to make frontier AI systems safer, and better understood by researchers and policymakers.. For example, you might: Design and run post-training pipelines to study how training choices affect model safety, robustness, and alignment properties; Develop interpretability-informed evaluations that reveal how and why models produce unsafe, deceptive, or otherwise undesirable behaviors, and use those insights to guide targeted mitigations; Collaborate with policymakers, engineers, and other researchers to translate post-training and interpretability findings into actionable safety standards, evaluation benchmarks, and best practices. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Experience with post-training and RL techniques such as RLHF, DPO, GRPO, and similar approaches. A track record of published research in machine learning, particularly in generati

Staff Software Engineer - AI Research Infrastructure P-1215 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. Job Description As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate, and observe large‑scale training and inference experiment workloads across thousands of GPUs, improve our dev tooling and ensure that researchers can iterate quickly without sacrificing reliability, efficiency, or security. You’ll partner closely with research scientists, ML engineers, and platform teams to turn experimental workloads into robust, repeatable pipelines, and to push the limits of what our infrastructure can support. The Impact you will have As a Staff Software Engineer on the AI Research Infra Team at Databricks, you will: Design and implement infrastructure that supports large‑scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud‑based systems) Enable researchers to go from idea to large‑scale experiment in minutes, not days, by building powerful abstractions for job submission, scheduling, and monitoring. Create tooling that improv

P-1549 At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. The Mission Databricks agents are only as good as the context they can retrieve. Whether an agent is answering a question about last quarter's revenue, debugging a failing job, generating SQL against a 10,000-table lakehouse, or summarizing a Wiki page, its quality is bounded by what it can find — and how well it understands what it finds. We are hiring a Senior Staff Applied AI Engineer to own context retrieval for Databricks agents across SaaS providers . This is a zero-to-one role with two deeply connected charters: Build the retrieval stack — query understanding, content understanding, ranking, retrieval, and evaluation — across the Enterprise SaaS data stored across multiple systems. Build the search subagents that sit on top of that stack and reason about what context is needed , how to retrieve it , and whether the right thing actually came back — closing the loop between an agent's intent and the substrate that serves it. If you have deep Information Retrieval wisdom, have shipped retrieval systems for RAG and agentic workloads, and want to build the substrate — and the agents on top of it — that make every Databricks agent measurably smarter, this role is for you. What You Will Do Build the full retrieval stack from scratch. Own the end-to-end system: query understanding, content understanding and indexing, hybrid retrieval, ranking, and evaluation. Make the architectural calls that will define how Databricks agents access context for years to come. Retrieve across heterogeneous data — structured and unstructured. Index and rank across structured assets (tables, columns, SQL queri

Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge We are looking for an Account Executive, Enterprise. Account Executives have a critical role and responsibility to deliver new client acquisition in zero-base accounts, while also ensuring successful relationships and revenue growth with existing customers. OneTrust is a fast-growing SaaS enterprise platform with a strong growth trajectory. We invest heavily in our Sales Team through demand generation, methodology-driven sales philosophy, weekly sales trainings, customer-driven roadmaps, and a readily-available executive team to help close deals. Your Mission The Account Executive (AE) is responsible for consistently generating, qualifying, and executing opportunities that support our customers in the pursuit of becoming more trusted organizations and drive revenue for OneTrust. AEs are expected to use their thorough knowledge of the industry and excellent value-based sales skills to create the best solutions and solve complex customer problems. AEs must bring useful insights and best practices to customers and prospects. As an Account Executive, Enterprise, you will:&n

Staff Software Engineer - AI Research Infrastructure P-1215 At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. Job Description As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate, and observe large‑scale training and inference experiment workloads across thousands of GPUs, improve our dev tooling and ensure that researchers can iterate quickly without sacrificing reliability, efficiency, or security. You’ll partner closely with research scientists, ML engineers, and platform teams to turn experimental workloads into robust, repeatable pipelines, and to push the limits of what our infrastructure can support. The Impact you will have As a Staff Software Engineer on the AI Research Infra Team at Databricks, you will: Design and implement infrastructure that supports large‑scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud‑based systems) Enable researchers to go from idea to large‑scale experiment in minutes, not days, by building powerful abstractions for job submission, scheduling, and monitoring. Create tooling that improv

About the Team At DoorDash, design means making experiences for the people who order, the people who prepare, and the people who deliver. As a Design Manager at DoorDash, you want to build things that matter to real people. You're at your best when you can move from idea to shipped product quickly, bringing experiences to life that reach and influence users at massive scale. You'll care about whether the product you make solved a real problem for real people, or changed how someone experiences their day. You'll work shoulder-to-shoulder with Engineering and Product Management, dig into the data, and use LLM-powered tools alongside traditional design tools. If the LLM powered tools don’t exist yet, you build them. About the Role Trust is the foundation of every interaction on DoorDash. We're looking for a design leader who can define and drive a vision for designing for integrity at scale. In this role, you will join the Integrity organization. You’ll lead a team of designers working across fraud prevention, trust, safety, and compliance — protecting millions of consumers, Dashers, and merchants while keeping the platform seamless and trustworthy. You will report into the Head of Design for our Customer Experience & Integrity organization. This role is hybrid- 1–2 days per week in one of our Design Hubs. You’re excited about this opportunity because you will… Set the technical direction for Design across your product area — decide what gets built, in what order, and why; connect multiple teams around shared platforms so the work compounds instead of duplicating Work on ambiguous problems and turn them into architecture decisions and working systems that teams actually use; earn trust with leadership not through decks, but through prototypes and shipped code that make your point for you Stay close to the code and the craft across multiple projects at once — you're not just reviewing, you're building; the work you ship will move real metrics across the product area

About the Team OpenAI’s Industrial Compute team is responsible for building and scaling large-scale compute capacity across first-party data centers, strategic partners, and industrial infrastructure environments. We focus on converting power, land, hardware, and operational execution into reliable compute capacity that can support frontier AI training and inference workloads. This team operates at the intersection of infrastructure delivery, hardware systems, utilities, supply chain, and capacity strategy—ensuring OpenAI can scale compute faster than traditional models allow. About the Role We are seeking a GPT Infrastructure Lead to drive the end-to-end conversion of industrial-scale infrastructure investments into usable token capacity for OpenAI workloads. In this role, you will own execution across complex compute programs where raw infrastructure capacity must be transformed into operational GPU throughput. You will coordinate across data center delivery, power, networking, hardware deployment, workload enablement, finance, and external partners to ensure capacity becomes productive tokens as quickly and efficiently as possible. This role is ideal for someone who can bridge physical infrastructure delivery with compute utilization outcomes. Success requires strong systems thinking, elite program leadership, and the ability to drive accountability across internal teams and strategic partners. In this role, you will Lead GPT Infrastructure programs across industrial compute environments, including first-party and partner-owned capacity. Convert delivered power, space, and hardware capacity into production-ready token throughput. Build integrated execution plans spanning construction, power energization, rack deployment, networking, cluster readiness, and workload onboarding. Partner with infrastructure engineering, hardware, networking, finance, supply chain, and operations teams. Drive external providers, EPCs, OEMs, utilities, and strategic partners toward agg

P-1495 About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Role Databricks is seeking a Senior Staff Product Operations Manager to serve as the chief architect of our internal operational ecosystem. This is a high-leverage leadership role embedded within Engineering, designed to orchestrate the complex intersection of technical innovation, product lifecycle maturity, and global Go-to-Market (GTM) acceleration. In this capacity, you will move beyond the management of existing processes to lead the creation of a formal Operational Association . You will be responsible for designing the high-fidelity frameworks that allow our engineering organization to remain agile while ensuring that every product investment is data-driven, transparent, and rigorously aligned with our long-term commercial strategy. This role is purpose-built for a strategic thinker who excels at navigating the "gray space" between a deep technical roadmap and the sophisticated financial requirements of a global enterprise platform. Impact Operational Orchestration: Define and govern the strategic engagement model between Engineering, Product, and GTM, ensuring that product lifecycle milestones are seamlessly integrated with field readiness and revenue velocity. Investment Intelligence: Act as a critical advisor to executive leadership, applying a consultant’s rigor to evaluate business inves

P-1495 About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. About the Role Databricks is seeking a Senior Staff Product Operations Manager to serve as the chief architect of our internal operational ecosystem. This is a high-leverage leadership role embedded within Engineering, designed to orchestrate the complex intersection of technical innovation, product lifecycle maturity, and global Go-to-Market (GTM) acceleration. In this capacity, you will move beyond the management of existing processes to lead the creation of a formal Operational Association . You will be responsible for designing the high-fidelity frameworks that allow our engineering organization to remain agile while ensuring that every product investment is data-driven, transparent, and rigorously aligned with our long-term commercial strategy. This role is purpose-built for a strategic thinker who excels at navigating the "gray space" between a deep technical roadmap and the sophisticated financial requirements of a global enterprise platform. Impact Operational Orchestration: Define and govern the strategic engagement model between Engineering, Product, and GTM, ensuring that product lifecycle milestones are seamlessly integrated with field readiness and revenue velocity. Investment Intelligence: Act as a critical advisor to executive leadership, applying a consultant’s rigor to evaluate business inves

MKTQ227R16 Databricks is building a new generation of native applications built on the Databricks Platform that help customers unlock value from their data faster. Lakewatch is the first of these apps, giving cybersecurity, governance, and risk teams an open, agentic Security Lakehouse that unifies security, IT, and business data into a single, governed environment for AI-powered detection, investigation, and response. We are looking for a Sr. Product Marketing Manager to support the marketing strategy for these emerging applications to support Lakewatch in its next phase of growth. In this role, you will shape and execute the go-to-market strategy and tactics for Lakewatch and other applications in the Agentic Apps portfolio, collaborating closely with demand generation, sales, partners, external agencies and contractors, and the broader Databricks marketing organization to drive awareness, adoption, and expansion for this first-of-its-kind motion at Databricks. This role sits within the product marketing organization and works cross-functionally with demand generation, product, sales, and alliances. The impact you will have: Hit or exceed Lakewatch and Agentic Apps pipeline and revenue goals by shaping and executing the GTM strategy that drives new logo acquisition and expansion within existing Databricks customers, with clear targets for sourced and influenced pipeline, ARR, and product adoption over the first 12–24 months. Execute content and field marketing activities across Agentic Apps by building and deploying scalable marketing programs that increase awareness, improve perception, and drive demand for Databricks Agentic Apps, with an emphasis on decision makers and senior executives in the line of business domain areas. Increase Lakewatch and Agentic Apps adoption and usage across priority customer segments by co-creating a compelling narrative and positioning that differentiates Databricks in its various application spaces with an emphasis on cyberse

Principal Research Scientist – Scaling P-1227 About Databricks AI At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development, by building and running the world’s best data and AI platform. The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all. About the Scaling Research Team The Databricks AI Scaling team focuses on pushing the boundaries of large language model (LLM) training and inference efficiency beyond what is required to support existing models. The team explores novel avenues for scaling and efficiency improvements across algorithms, systems, and infrastructure, requiring researchers who can both drive independent research agendas and dive deep into low‑level implementation details with engineering partners. Role Summary As a Principal Research Scientist – Scaling, you will lead a team of world‑class researchers and engineers to advance the state of the art in large‑scale machine learning, focusing on post-training, RL and inference efficiency, optimization, and scaling. You will define and execute a research roadmap that advances the Databricks AI platform and delivers tangible improvements to how customers train, serve, and adapt LLMs at scale, working closely with product, data, and engineering leaders to bring cutting‑edge methods into production. The Impact You Will Have Lead and grow a multidisciplinary research team focused on foundational and applied AI problems, with a particular emphasis on LLM scaling, efficiency, and systems performance. Define the scaling research roadmap in alignment with Databricks’ strategic obj

P-1605 About Databricks At Databricks, we are passionate about enabling data teams to solve the world's toughest problems — from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers — and customer obsessed — we leap at every opportunity to solve technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started. The Role At Databricks, we don’t just use the cloud; we are "cloud maximalists." Unlike most companies that treat multi-cloud as a backup strategy, we run our platform across every region of every major cloud provider (AWS, Azure, and GCP) simultaneously. This creates a massive, high-consequence engineering surface area that requires a unique breed of Production Engineer. In this role, you won’t just run our cloud environments; you will own and evolve the secure infrastructure, access patterns, and guardrails that keep Databricks’ global platform safe and compliant in production. You will be responsible for the "sovereign layer" of our infrastructure, ensuring that our Data Intelligence Platform operates with 100% reliability and security in highly regulated, air-gapped, and sovereign environments. If you are an engineer who views infrastructure as a software problem and thrives on the complexity of global-scale networking, IAM, and automation, this is your team. The Impact You’ll Have Security-Focused Cloud Operations Design, automate, and operate the IAM, account/subscription, and project lifecycle across AWS, Azure, and GCP, enforcing least-privilege and standardized access patterns at scale. Review, implement, and continuously improve cloud identity and access policies (IAM, Okta, Opal) to align with Data