Data Engineer in Singapore

Staff Engineer, Front End Labor Data Engineering — Fab 10A, Singapore. Apply via Workday.

Reolink , a leader in intelligent visual technology for homes and businesses, was founded in 2009 by a group of engineers with a strong commitment to and passion for smarter security solutions. Our products are now trusted by millions of users across more than 110 countries and regions worldwide. Building on this trust, we continue expanding our presence and bringing our innovations to more markets around the globe. Reolink remains committed to delivering advanced, reliable, and user‑centric solutions that empower people to protect what matters most. Position: E-commerce Data Analysts 5 Work Days Per Week Office Near Tai Seng MRT, Singapore Medical Benefits Provided Entitled to Yearly Bonus & Performance Bonus Background of E-Commerce Team Our e-commerce platform focus on Reolink Official Website & Amazon for different region particularly for the Australia and Europes & United States. Responsible driving business decisions through data analysis and visualization, job scopes include: Driving actionable insights: Analyzing data to generate insights that improve performance, profitability, and guest experience across various e-commerce platforms. Data analysis and reporting: Building data pipelines, self-service dashboards, and developing new in-house API features to drive growth and extend reach into other ecosystems/platforms. Collaboration with teams: Working with product management, engineering, and design teams to ensure data-driven decisions align with business goals. Data quality and integrity: Validating data quality, investigating data issues, and collaborating with data engineering teams to improve data pipelines and definitions. Supporting business decisions: Providing professional data support for business product decisions in e-commerce scenarios and building an e-commerce product metric system. E-commerce Data Analysts play a crucial role in the e-commerce industry, leveraging data to enhance business strategies a

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. Design and productionize models rather than just prototype them, including

A Career with Cubist Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures, and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources. What You’ll Do We are passionate about data. We collaborate to build elegant, effective, scalable, and highly reliable solutions to empower predictive modeling in finance. You will join a team that plays a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure and the timely delivery of comprehensive and error-free data to Cubist’s portfolio managers across the globe. Specifically, you will: Serve as a frontline owner for thousands of mission-critical data ETL pipelines that power trading and investment decision-making, ensuring reliability, accuracy, and timeliness. Actively manage and resolve data incidents in a fast-paced trading environment, partnering closely with portfolio managers, data scientists, and external data vendors. Design and build tooling, automation, and robust documentation to improve operational efficiency, scalability, and data quality across the platform. Play a hands-on role in daily data operations, including data validation, remediation, and enrichment, with opportunities to continuously improve and modernize workflows through engineering best practices. What’s Required Bachelor’s degree with a focus in computer science or a related field. Strong proficiency in SQL Server and Python programming, with experience in AWS and both Windows and Linux environments; familiarity with Databricks is a plus. Exceptional attention to detail with a strong appreciation for well-defined processes and systems. 3+ years of experience in a client-facing support or operations role. Excellent organizational, communication, and interpersonal

Data Analytics Engineer — MSB, Singapore. Apply via Workday.

IT Engineer (Data Services) — Fab 10W, Singapore. Apply via Workday.

IT Engineer (Data Services) — Fab 10W, Singapore. Apply via Workday.

IT Engineer (Data Services) — Fab 10W, Singapore. Apply via Workday.

Product Engineer (Advance Data Analytics), Heterogeneous Integration Group (HIG), High Bandwidth Memory (HBM) Product Engineering — Fab 10A, Singapore. Apply via Workday.

Product Engineer (Advance Data Analytics), Heterogeneous Integration Group (HIG), High Bandwidth Memory (HBM) Product Engineering — Fab 10A, Singapore. Apply via Workday.

Snr/Product Engineer (Advance Data Analytics), Heterogeneous Integration Group (HIG), High Bandwidth Memory (HBM) Product Engineering — Fab 10A, Singapore. Apply via Workday.

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world's largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone's reach while doing the most important work of your career. About the team Our Growth team is on a mission to acquire, convert, and grow millions of merchants globally across the full Stripe suite of financial products. We're a cross-functional team of engineers, scientists, marketers, designers, and product managers that deliver the insights, algorithms, internal systems and tools, and user-facing experiences that fuel our growth. We help businesses around the world find Stripe, get started, and grow. As part of the Growth Engineering team, you'll build the systems, products, internal tools, and customer-facing experiences that power intelligence behind our go-to-market and product-led growth. This includes building ML-powered recommendations and growth experimentation engines, multi-channel notification systems, and key growth-related customer experiences (e.g., onboarding flows, user dashboards, product recommendations). What you'll do As a full-stack engineer on the Growth team, you'll build and ship experiments and product improvements across stripe.com and the Dashboard to help businesses find and get started on Stripe. You'll work on critical parts of the funnel for self-serve users, ensuring their experience on Stripe is consistently high-quality. With other engineers and data scientists, you'll turn ML-powered recommendations, messaging, and experimentation into impact that moves company metrics. Responsibilities Build and maintain scalable systems and customer experiences that help businesses discover, on

Data Center SSD Performance Validation Engineer — MSB, Singapore. Apply via Workday.

Ready to do the most impactful work of your career? At Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for "good enough," you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.” learn more about working at Coinbase . Software Engineer, Data Layer As a Software Engineer on the Data Layer team within the Platform group, you'll shape the API (GraphQL) platform that connects every client application to Coinbase's backend services, handling the majority of user traffic across Consumer, Base, and Institutional products. You'll own the critical systems that route and serve API requests at scale, improving reliability, performance, and developer experience for hundreds of engineers building on this foundation layer. What you'll do: Own and deliver projects end to end, from scoping and system design through implementation, rollout, and production validation, driving measurable progress on the team's highest-priority initiatives. Design and build high-reliability, low-latency systems serving millions of users, tackling challenges like caching, upstream service optimization, and efficient connection management at scale. Build and improve the API framework and tooling that hundreds of engineers depend on, making it fast and easy for teams across the company to build, test, and ship independently. Drive operational excellence across T0 services: own SLOs, improve observability, lead incident response, and reduce operational toil so the team can invest in high-leverage work. Partner cross-functionally with product engineering teams to design API schemas, support service launches, and ens

Staff Product Engineer (GenAI, AI/ML & Advanced Data Analytics) — Fab 10A, Singapore. Apply via Workday.