Data Engineer Jobs

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction flow of every dollar a business spends. We automate how over $200B in annualized spend flows in and out of 70,000+ companies: authorizing payments, flagging risk, categorizing spend, and closing books. The problems are high-stakes, data-dense, and unforgiving. We hire people with high agency and high urgency. We look for slope over intercept. We care less about where you trained and more about what you’ve built. At Ramp, everyone is a builder who owns problems end to end and makes consequential decisions that shape the outcome. The median Ramp customer saves 5% and grows revenue 16% in their first year – far in excess of businesses operating without Ramp. We believe every ambitious company deserves the same. If you want to build systems that directly shape how companies move and manage billions, Ramp is the place to do it. About the Role The Engineering Platform team helps 300+ Ramp engineers move faster without breaking things. We work across the full software development lifecycle, including local development, CI/CD, testing, service frameworks, reliability, architecture, performance, and maintenance. Platform engineers on this team do not wait for a roadmap to be handed to them. They find high-leverage problems, validate them with engineers and data, ship solutions, and iterate until those solutions are trusted, adopted, and durable. Agentic development has expanded our mission. We are building the systems that let engineers and AI agents work together effectively in Ramp’s large, complex codebases: clear abstractions, orchestration, reliable workflows, fast feedback loops, and strong guardrails are now even more important. These platform investments unlock agentic workflows that can plan, execute, test, review, and ship meaningful changes, helping every engineer and agent at Ramp maximize their impact. What You'll Do Improve Ramp’s development workflows across CI/

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Role We are seeking a highly technical, data-driven Growth Engineer to help scale our product and expand key user metrics across acquisition, activation, retention, and monetization. Growth Engineering sits at the intersection of engineering, product, and marketing—leveraging code, experimentation, and analytics to uncover opportunities and deliver measurable impact. What You’ll Do Drive Experimentation & Optimization Design, implement, and analyze rapid A/B and multivariate tests to validate hypotheses and improve key KPIs. Identify bottlenecks in user funnels and develop technical solutions to improve conversion rates throughout the user lifecycle. Build and Scale Growth Features Build growth-oriented product features such as onboarding flows, referral systems, and automated engagement loops. Develop scalable code and infrastructure that supports growth initiatives and experimentation frameworks. Leverage Data & Metrics Collaborate with data teams to instrument tracking, build dashboards, and derive insights from user behavior data. Use SQL and analytics tools to deeply analyze cohorts, engagement metrics, and experiment outcomes. Cross-Functional Collaboration Partner closely with product managers, designers, marketers, and data scientists to align on growth goals and execution plans. Translate business goals into technical requirements and implement pragmatic solutions that drive sustainable growth. Continuous Innovation Stay updated on industry trends and growth-oriented technologies and propose new tactics to accelerate growth. Automate repetitive tasks and build internal tools to empower faster experimentation and execution. Required Qualifications Bachelor’s degree in Computer Science, Enginee

Our Internal Data team is on a mission to power decisions and applications across MongoDB, oriented around the business areas of GTM, Product & Technology, Finance and HR. With this role, we are focusing on delivery of scalable, insightful, and impactful data products for our Product and Technology (P&T) teams - the org that builds MongoDB products for our external customers. These products drive smarter decisions, automate workflows, enable AI agents and deliver actionable insights that accelerate growth. If shaping the future of data-as-a-product excites you, then this opportunity is for you. As a Senior Data Product Manager on our Data team — which includes Data Pipeline/Platform Engineering, Data Architecture, and Data Governance — you will lead efforts to build, enhance, and scale the data products MongoDB employees use every day across a growing, high-impact company. You’ll deliver data products like data pipelines, datasets, reports/dashboards, APIs, ML models, playbooks, and frameworks while enhancing more traditional data management tools/services to power both AI and BI. These data products form the backbone of our internal data ecosystem and are instrumental in empowering teams to achieve their KPIs and innovate faster. In this role you will also have the opportunity to drive the vision and strategy for internal data as a product, with a focus on telemetry and product adoption/engagement/churn signals. By developing tools and systems that provide deep insights into how customers use or don’t use MongoDB’s products, you will empower teams to understand customer behaviors and improve the end-user experience. The goal is to enable data-driven decisions that enhance product design, drive customer value, and fuel innovation across the MongoDB portfolio. This role can be based out of our Palo Alto, San Francisco, or New York City office or remotely in the East Coast region. Responsibilities Lead Product Strategy and Ownership Define product vision, stra

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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lake using open formats like Apache Iceberg, delivering deep correlation and long-term analytics at dramatically lower cost. A dynamic Knowledge Graph and chat-based AI SRE provide rich context and guided workflows so teams can move from detection to root cause and resolution significantly faster. The Infrastructure team at Observe by Snowflake is responsible for building, scaling, and operating the development and production environments that power our observability platform. We are a small, highly collaborative team with a broad scope, focused on delivering reliable infrastructure while continuously improving the systems that support our engineers and customers. What You’ll Do Design, build, and operate scalable cloud infrastructure in AWS supporting a high-scale observability platform. Improve system reliability, performance, and operational visibility across development and production environments. Develop and maintain CI/CD pipelines and internal tooling to improve developer productivity and deployment safety. Identify and mitigate security risks, and help maintain intern

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. The Snowhouse Foundation team builds our globally distributed data warehouse. We manage a vast array of petabyte scale data sets that are continuously ingested, processed and replicated from across all Snowflake environments and external data sources. Snowhouse powers all of Snowflake’s core business, engineering and data science needs and provides customers with full visibility into their account activities, usage, and resource consumption from all their global environments. The team is investing in multiple critical areas, including a pipeline authoring platform, high performance/high efficiency data export, ingestion and data layout. Our team is also responsible for a fundamental product for Snowflake’s customers: the Snowflake system database/application that provides customers with all usage insights they need to reason about their global Snowflake footprint as well as 1st party business logic such as ML powered functions and Budgeting applications. AS A PRINCIPAL SOFTWARE ENGINEER IN SNOWHOUSE FOUNDATION, YOU WILL: Design and implement innovative highly available distributed platforms and pipelines and enhance the overall Snowflake data infrastructure Lead and drive projects from idea formulation to design, implementation and successful productionization. Collaborate

About Goods & Services Goods & Services is a product design and engineering company. We solve mission-critical challenges for some of the world’s largest enterprises, with deep expertise in highly regulated industries—including life sciences and financial services . Our design-led approach allows us to apply cutting-edge capabilities in AI, Data and Hardware Engineering to companies of any size. Headquartered in the United States , we operate regional development centers in Mexico and the United Kingdom . This global footprint—anchored by our nearshore model—enables us to deliver at scale with the speed, efficiency, and cultural alignment our clients expect. At Goods and Services, we value diversity and are committed to creating an inclusive workplace where everyone can thrive. We are proud to be an Equal Opportunity Employer and welcome qualified applicants from all backgrounds. About the job Goods & Services is looking for a Senior Mobile Engineer (AI-Assisted) to design, develop, and maintain a cross-platform mobile application serving both iOS and Android users. The ideal candidate has strong experience building production-ready mobile applications using React, TypeScript, and Capacitor, and has successfully managed deployments to both the Apple App Store and Google Play Store. This role requires a hands-on engineer who is comfortable working across web and mobile technologies, developing native integrations when needed, and maintaining high standards for code quality and type safety. What you’ll do: Design, develop, and maintain mobile applications for iOS and Android using React and Capacitor. Build scalable, maintainable, and high-performance user interfaces using React 18 and TypeScript. Develop and maintain native mobile integrations and Capacitor plugins as needed. Configure and manage build environments using Vite. Collaborate with backend, product, and design teams to deliver seamless user exp

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Software Engineer Overview Interested in building the next generation platform that empowers end-to-end marketing campaign management inclusive of audience targeting, campaign execution, and measurement? Our platforms operate at global scale, enabling organizations across markets worldwide to leverage data-driven marketing capabilities. The overarching goal of data-driven marketing is to deliver the right content, to the right person, at the right time. The Marketing Services (MS) Technology team is looking for a Senior Software Development Engineer to provide technical ownership, with an emphasis on engineering efficiency, innovation, and on-time delivery. The ideal candidate is passionate about building highly scalable, cloud-native platforms using modern software engineering and data technologies. You will have the opportunity to work across technologies including Java, Spring Boot, React, GraphQL, Databricks, AWS, Spark, Hadoop, event-driven architectures, and real-time data platforms. Our teams leverage GenAI and Agentic AI capabilities throughout the product development lifecycle to accelerate delivery, improve quality, enhance automation, and increase engineering productivity. This role offers an opportunity to help shape Mastercard's ongoing cloud transformation journey while transform

About Goods & Services Goods & Services is a product design and engineering company. We solve mission-critical challenges for some of the world’s largest enterprises, with deep expertise in highly regulated industries—including life sciences and financial services . Our design-led approach allows us to apply cutting-edge capabilities in AI, Data and Hardware Engineering to companies of any size. Headquartered in the United States , we operate regional development centers in Mexico and the United Kingdom . This global footprint—anchored by our nearshore model—enables us to deliver at scale with the speed, efficiency, and cultural alignment our clients expect. At Goods and Services, we value diversity and are committed to creating an inclusive workplace where everyone can thrive. We are proud to be an Equal Opportunity Employer and welcome qualified applicants from all backgrounds. About the job Goods & Services is looking for a Senior Software Engineer in Test who will deep into the challenging problems, come up with the solutions, and build innovative features which transform customers’ experience and bring efficiency by applying in the software build and delivery process. What you’ll do: Work closely with the Test automation engineers and cross functional product owners to translate the acceptance criteria to technical documents to write the automation scripts and integrate it with Test Automation framework and CI/CD pipeline. Provide the progress status update to Project manager and reporting manager. Ensure you work in align with the given project schedule for you and the team. Ensure all the functional requirements, business process flows are understood, and tested on the test, UAT env in adherence with the Quality assurance process and procedure . What you’ll need: Bachelor’s degree in computer science or related field. 5+ years of experience in manual testing, automated testing and test plan preparation.

Amplitude is the leading AI analytics platform, helping over 4,700 customers—including Atlassian, Burger King, NBCUniversal, and Square—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Winter 2026 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. Senior Software Engineer - Analytics Compute Platform Team About the Role & Team Every chart, insight, and experiment result a customer sees in Amplitude passes through the compute layer that this team owns. Our team sits between Amplitude's front-end analytics products/ rest APIs/ MCPs and Nova, our proprietary analytics database, and owns the compute API that translates a user's question into a fast, correct answer. Our mandate: enable a highly performant, reliable, and flexible way to compute insights. Those three goals are often in tension the more flexible we make the system, the harder it is to keep it fast and simple, and a lot of the interesting engineering work on this team lives in that tradeoff. Day to day, you'll work closely with engineers on data management, marketing analytics, Session Replay, Experiment, CDP, Query,

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be. Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. About the Ads Data Science Team: The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling. About the Role: Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal

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. Observe by Snowflake is an AI-powered observability platform built on the Snowflake AI Data Cloud and engineered for scale. We ingest and store logs, metrics, traces, and events on an open, scalable data lakehouse, using open formats like Apache Iceberg, at dramatically lower cost. A dynamic Context Graph and chat-based AI SRE provide rich context and automated workflows so teams can move from detection to root cause of production issue and resolution 10x faster. Leading engineering teams at companies like Capital One, Topgolf, and Dialpad rely on Observe to troubleshoot hundreds of terabytes of telemetry daily while maintaining reliability at enterprise scale. As part of Snowflake, Observe combines startup-style ownership and velocity with the global reach, operational excellence, and ecosystem of one of the world’s leading data platforms. We are hiring a Senior Frontend Engineer, AI Products team at Observe by Snowflake. As an AI Product engineer you'll always be thinking first about the user experience and how to create the best product, technical choices, and implementation decisions that stem from that product first thinking. This team builds the AI-powered products and developer tooling at the core of Observe's platform, including our flagship AI SRE product, real-tim

Senior Software Engineer - Analytics Compute Platform Team About the Role & Team Every chart, insight, and experiment result a customer sees in Amplitude passes through the compute layer that this team owns. Our team sits between Amplitude's front-end analytics products/ rest APIs/ MCPs and Nova, our proprietary analytics database, and owns the compute API that translates a user's question into a fast, correct answer. Our mandate: enable a highly performant, reliable, and flexible way to compute insights. Those three goals are often in tension the more flexible we make the system, the harder it is to keep it fast and simple, and a lot of the interesting engineering work on this team lives in that tradeoff. Day to day, you'll work closely with engineers on data management, marketing analytics, Session Replay, Experiment, CDP, Query, and various product teams, since they're all consumers of what we build. As a Senior Software Engineer, you will Design and build core parts of the query/compute engine that powers analysis across Amplitude's product suite Evolve the compute API and semantic layer that other engineering teams build features on top of, so that it can support a more generic table Help unify and evolve our core data model, including how non-event data (profile properties, lookup tables, etc.) is represented alongside event data Improve the performance, reliability, and scalability of query planning and execution on the Amplitude query engine Partner with teams across Session Replay, Experiment, CDP, Query, and frontend to understand their needs and shape the compute layer around them Take ownership of projects end-to-end, from design through rollout You'll be a great addition to the team if you have Strong backend or distributed-systems engineering experience, ideally touching OLAP databases, query engines, or data infrastructure Experience with SQL, query planning/execution, or building APIs that many other engineering teams depend on Comfort reasoning