Senior Software Engineer, Data Engineering

About the Role The Data engineering team has been created keeping in mind the importance and criticality of data for the overall success of Chime. The mission of this group is to build scalable data artifacts and insights that enable accurate, governed, data-driven decision-making.. As a core member of the team, you will have the opportunity to build scalable data pipelines and frameworks. Additionally, you will have the unique opportunity to architect and build workflows that could potentially become de facto standards for the fintech industry. In this role, you can expect to Be a hands-on data engineer, building, scaling and optimizing ETL pipelines Design data schemas and scale them data for 10x data growth Ownership of all aspects of data - data quality, data governance, schema design, data quality and security Develop scalable data architecture and standardized data models that enable self-serve data insights using AI. Own the ETL workflows and make sure the pipeline meets data quality and availability requirements Work closely with partner teams, like Data Science, Analytics and DevOps To thrive in this role, you have 5+ years experience transforming data to governed and lucid datasets 5+ years of hands-on experience to build and deploy production-quality data pipelines 5+ years of experience working with stakeholders to provide business insights 5+ years of experience writing SQL, Spark, AWS Glue, EMR, Airflow, Python 3+ years of hands-on experience using any MPP database system like Snowflake, AWS Redshift or Teradata Track record of successful partnerships with Analytics, Data Science and DevOps teams Understanding of key metrics for data pipelines and has built solutions to provide visibility to partner teams Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary. #LI-Onsite #LI-WW1 Below is the base salary offered for t

About the Role Chime’s Data Platform team builds the infrastructure every engineering and analytics team depends on - ingestion, transformation, quality, governance, and self-serve tooling across batch and streaming workloads. You’ll own core platform systems at scale, design the frameworks other teams build on, and set the technical standards for how data moves through Chime. High autonomy, real architectural trade-offs, production impact from day one. We’re hiring multiple engineers into this role at the senior level. In this role, you can expect to Design, build, and operate self-serve ETL/ELT frameworks supporting both batch and streaming workloads, with direct ownership of pipeline reliability, data quality SLAs, and schema evolution Drive the technical roadmap for our data platform - evaluate build-vs-buy decisions, define integration patterns, and set standards that engineering teams across the company adopt Partner with Product Engineering, Data Science, Analytics, and Marketing as a technical lead to design data contracts, onboard new data domains, and scale ingestion without sacrificing governance Architect and enforce data lineage, schema registry, and access controls across all domains - ensuring compliance with fintech regulatory requirements (SOX, PII handling) Own the platform - monitor, alert, debug, and resolve incidents across the data platform with the urgency expected of infrastructure that powers financial products Raise the technical bar of the team through code review, design reviews, and hands-on mentorship of junior and mid-level engineers Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary. To thrive in this role, you have 5+ years building, shipping, and operating data infrastructure in production - not just writing pipelines, but owning their reliability, performance, and cost at scale Strong system design skills - you’ve written desig

About the role Chime’s Machine Learning Platform (MLP) team builds and operates the infrastructure, tooling, and developer experience that powers machine learning across the company. We enable data scientists and ML engineers to develop, train, deploy, and monitor models reliably and efficiently. As a Senior Software Engineer on the Machine Learning Platform team, you will design and build scalable systems spanning traditional machine learning and emerging AI workloads, including model training, feature computation, real-time inference, foundation-model access, evaluation, and agentic orchestration. You’ll work at the intersection of distributed systems, cloud infrastructure, applied machine learning, and AI product engineering. This role focuses on creating secure, reliable, and reusable platform capabilities that help teams choose the right approach, from conventional predictive models to LLM-powered and multi-step agentic systems, while maintaining strong standards for evaluation, observability, governance, privacy, and cost efficiency. In this role, you can expect to Design, build, and operate scalable ML and AI infrastructure on AWS. Design and operate shared platform capabilities for LLM and agentic workloads, including model access, prompt and configuration lifecycle, retrieval, tool integration, state management, and workflow orchestration. Build evaluation frameworks for non-deterministic AI systems, including offline benchmarks, regression testing, online quality signals, human feedback, and failure analysis. Establish observability, reliability, and governance for models and agents, covering traces, model and prompt versions, tool calls, latency, token usage, quality, safety, privacy, and cost. Help teams make principled architecture decisions across traditional ML, LLM-powered applications, and agentic workflows, and contribute to the platform’s technical roadmap. Build distributed training, batch inference, and large-scale processing systems using

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Senior Software Engineer on Spark Platform, you will set the technical direction for our in-house Spark deployment and shape the architecture that will run DoorDash's data, analytics, and ML compute for the next five years and beyond. You will own the deep, cross-cutting problems that span the runtime, the shuffle service, the scheduler, and the overall service reliability — making the architectural calls that compound across the platform's lifetime. You will partner with the Engineering Manager on technical roadmap, hiring, and team shape, and act as the senior technical voice in cross-team partnerships with Data Engineering, ML Platform, and product engineering teams that depend on the platform. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Set the multi-year technical direction for an in-house Spark-on-Kubernetes platform — runtime, shuffle, scheduler, reliability — and make the architectural calls that compound for years. Own the deepest distributed-systems problems on the team: shuffle architecture, multi-tenant scheduling, runtime performance, and the failure modes that only show up at scale. Partner with the Engineering Manager on technical roadmap, hiring, inte

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Intro : Pinterest’s Service Configuration & Coordination team builds the platforms, APIs, and tooling that make dynamic configuration and service coordination safe, scalable, and reliable for every service across regions and clouds, serving as the central hub for cross-functional alignment and system orchestration. As a Senior Staff Software Engineer (IC17) , you’ll own the end-to-end technical strategy and long-term vision for our configuration and coordination infrastructure. You’ll define the future of these mission-critical systems, partnering closely with Traffic, Compute, Observability, and Cloud Architecture teams to deliver robust, high-performance solutions at scale. What you’ll do: Orchestrate the long-term technical vision for configuration ecosystems to ensure feature flags, ML settings, and experiments utilize unified pave

Why join us Brex is the intelligent finance platform that enables companies to spend smarter and move faster in more than 200 markets. By combining global corporate cards and banking with intuitive spend management, bill pay, and travel software, Brex enables founders and finance teams to accelerate operations, gain real-time visibility, and control spend effortlessly. Brex’s AI-native automation and world-class service eliminate manual expense and accounting tasks for customers so they can focus on what matters most. Tens of thousands of the world's best companies run on Brex, including DoorDash, Coinbase, Robinhood, Zoom, Plaid, Reddit, and SeatGeek. Working at Brex allows you to push your limits, challenge the status quo, and collaborate with some of the brightest minds in the industry. We’re committed to building a diverse team and inclusive culture and believe your potential should only be limited by how big you can dream. We make this a reality by empowering you with the tools, resources, and support you need to grow your career. Data at Brex Our Scientists and Engineers work together to make data — and insights derived from data — a core asset across Brex. But it’s more than just crunching numbers. The Data team at Brex develops infrastructure, statistical models, and products using financial data. Our work is ingrained in Brex’s decision-making process, the efficiency of our operations, our risk management policies, and the unparalleled experience we provide our consumers. What you’ll do This position is on our Data Enablement Platform team. The Brex product requires a huge amount of data to power our client experiences. With a largely async architecture, proliferation of services and multiple operations systems, this data originates from many different sources and in different forms. To ensure that our product experience is unbounded in how it leverages this data, the Data Enablement Platform team owns and operates the systems required to deliver it t