Lead Data Engineering Manager Jobs

As a Staff Engineer on Datadog's Compute – Disruption and Workload Placement team, you'll help define how our Kubernetes fleet scales to meet the demands of rapidly growing AI and cloud-native workloads. You'll work on the systems that ensure engineering teams have the right compute capacity, in the right region, at the right time across AWS, Google Cloud, and Azure. This is a highly technical, high-impact role where you'll shape the future of capacity orchestration, influence platform architecture, and solve infrastructure challenges that directly support Datadog's continued growth. 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: Lead the technical direction of capacity management and workload placement for Datadog's Kubernetes platform spanning 100,000+ virtual machines across multiple cloud providers. Design and build systems that optimize how engineering workloads are scheduled and deployed across regions while balancing capacity constraints, reliability, and performance. Partner across infrastructure teams to evolve multi-region and multi-cloud capacity orchestration as Datadog continues to scale. Develop production software in Go to improve Kubernetes platform capabilities, automation, and operational efficiency. Use data and capacity signals to influence infrastructure decisions, forecast growth, and improve workload placement strategies. Who You Are: You have significant experience designing and operating large-scale Kubernetes-based infrastructure or platform systems. You are an experienced software engineer with strong programming skills, ideally in Go or a comparable systems programming language. You have hands-on experience with at least one major cloud provider (AWS, Google Cloud, or Azure) and understand distributed cloud infrastructure. Yo

This role is part of Datadog’s Security Agent team, which powers critical security capabilities across Workload Protection, Vulnerability Management, Cloud Security products, and other emerging security offerings. As a Staff Software Engineer, you will lead the design and development of low-level Linux instrumentation and runtime security technologies that help customers detect threats, monitor system activity, and protect cloud-native workloads at scale. You will work on complex technical challenges involving eBPF, Linux kernel internals, performance-sensitive systems, and large-scale data collection while influencing technical direction across multiple product teams. This role offers significant ownership, broad organizational impact, and the opportunity to shape the future of Datadog’s security platform. 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: Lead the architecture and development of security agent capabilities that power runtime threat detection and workload protection across Datadog Security products. Design and build reusable eBPF-based monitoring functionality for process, file, and network visibility within Linux environments. Drive end-to-end delivery of new features, from technical strategy and design through implementation, testing, and rollout. Establish and evolve testing methodologies that improve platform coverage, detection quality, reliability, and performance. Partner with product, security, infrastructure, and engineering teams to deliver shared platform capabilities used across multiple Datadog products. Provide technical leadership by influencing engineering direction, mentoring peers, and helping resolve complex cross-functional challenges. Who You Are: You have significant experience building software in Linux environments,

Please note that the job is only available from the locations outlined. 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

This role is part of Datadog’s Security Agent team, which powers critical security capabilities across Workload Protection, Vulnerability Management, Cloud Security products, and other emerging security offerings. As a Staff Software Engineer, you will lead the design and development of low-level Linux instrumentation and runtime security technologies that help customers detect threats, monitor system activity, and protect cloud-native workloads at scale. You will work on complex technical challenges involving eBPF, Linux kernel internals, performance-sensitive systems, and large-scale data collection while influencing technical direction across multiple product teams. This role offers significant ownership, broad organizational impact, and the opportunity to shape the future of Datadog’s security platform. 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: Lead the architecture and development of security agent capabilities that power runtime threat detection and workload protection across Datadog Security products. Design and build reusable eBPF-based monitoring functionality for process, file, and network visibility within Linux environments. Drive end-to-end delivery of new features, from technical strategy and design through implementation, testing, and rollout. Establish and evolve testing methodologies that improve platform coverage, detection quality, reliability, and performance. Partner with product, security, infrastructure, and engineering teams to deliver shared platform capabilities used across multiple Datadog products. Provide technical leadership by influencing engineering direction, mentoring peers, and helping resolve complex cross-functional challenges. Who You Are: You have significant experience building software in Linux environments,

This role is part of Datadog’s Security Agent team, which powers critical security capabilities across Workload Protection, Vulnerability Management, Cloud Security products, and other emerging security offerings. As a Staff Software Engineer, you will lead the design and development of low-level Linux instrumentation and runtime security technologies that help customers detect threats, monitor system activity, and protect cloud-native workloads at scale. You will work on complex technical challenges involving eBPF, Linux kernel internals, performance-sensitive systems, and large-scale data collection while influencing technical direction across multiple product teams. This role offers significant ownership, broad organizational impact, and the opportunity to shape the future of Datadog’s security platform. 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: Lead the architecture and development of security agent capabilities that power runtime threat detection and workload protection across Datadog Security products. Design and build reusable eBPF-based monitoring functionality for process, file, and network visibility within Linux environments. Drive end-to-end delivery of new features, from technical strategy and design through implementation, testing, and rollout. Establish and evolve testing methodologies that improve platform coverage, detection quality, reliability, and performance. Partner with product, security, infrastructure, and engineering teams to deliver shared platform capabilities used across multiple Datadog products. Provide technical leadership by influencing engineering direction, mentoring peers, and helping resolve complex cross-functional challenges. Who You Are: You have significant experience building software in Linux environments,

We are looking to speak to candidates who are based in Gurugram for our hybrid working model. About the Role We are looking for a Staff Integration Engineer (Workato & API Integration) to join our GTMTech team. This strategic role will lead the design, implementation, and governance of enterprise-grade integrations that power our core business processes across GTM systems, with a primary focus on Workato-based integrations and modern API management patterns. You will own the architecture for critical integration domains such as Quote-to-Cash and other high-impact GTMTech programs, ensuring our integration landscape is scalable, secure, observable, and aligned with best practices for event-driven and API-first designs. You will partner with engineering, architecture, security, and business stakeholders to define standards, mentor other integration engineers, and drive continuous improvement in how we connect systems and data. The GTMTech team is focused on high-impact, large-scale technology programs, such as Quote-to-Cash. Our mission is to enhance company efficiency, boost profitability, and enable data-driven decision-making by streamlining systems, optimizing processes, and minimizing manual, low-value work through automation and AI. Key Responsibilities Lead the end-to-end architecture, design, and implementation of Workato-based integrations and APIs across GTM systems (e.g., Salesforce, NetSuite, HRIS, Google Workspace) with a focus on scalability, reliability, and security Define and evolve integration standards, patterns, and best practices, including canonical integration patterns, error-handling strategies, observability, and operational runbooks Design and review complex, event-driven integration workflows leveraging technologies such as Kafka or equivalent messaging platforms, ensuring robust handling of topics, producers/consumers, durability, and retry mechanisms Drive API-first and MCP-native design for GTM integrations, leveraging RESTful APIs al

Who we are About Stripe Stripe, LLC. 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. What you’ll do Responsibilities Lead technical discussions and implement scalable technical solutions for open-ended, medium-to-large-sized technical problems in the issued cards and financial accounts space, including account management/compliance, onboarding, fraud prevention, and more (50%); Write technical project briefs and workstream roadmaps for medium-to-large-sized technical problems in the banking-as-a-service space (5%); Provide mentorship & technical training around the codebase to junior engineers and newer engineers (5%); Write technical documentation around compliance and fraud within the card issuing domain (5%); Partner directly with cross functional teams, like Product and Fraud Strategy, to translate real-world requirements into technical outcomes (5%); Regularly go on-call for your engineering team (10%); Review API and technical designs for various engineering teams (20%). Who you are Minimum requirements Bachelor's degree or foreign equivalent in Computer Science or related field followed by 3 years of experience in Software Engineering. Position also requires experience with the following: 3 years of experience with typed (Java, C++ or Scala) or untyped programming languages (Javascript, Ruby, Python); 2 years of experience with building end-to-end software solutions for fraud, compliance, and/or onboarding in the banking-as-a-service space; 2 years of experience with Data

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. Our Industrial Compute organization develops and deploys large-scale AI campuses designed to support the next generation of frontier model training and inference workloads. The Hardware Operations team is responsible for ensuring the reliability, availability, and lifecycle health of OpenAI’s compute infrastructure. We partner closely with Data Center Operations, Fleet Health Engineering, Manufacturing, Network Infrastructure, Capacity Planning, and our infrastructure partners to maintain world-class operational performance across rapidly expanding AI environments. As we scale globally, we are building the operational frameworks, reliability standards, and sustaining engineering practices required to support thousands of GPUs and servers across multiple campuses. About the Role We are seeking a Datacenter Hardware Technician Lead to serve as the senior on-site technical authority for hardware reliability and fleet health at one of OpenAI’s flagship AI campuses. This role operates at the intersection of hardware operations, sustaining engineering, and fleet reliability. You will partner closely with Cloud Service Provider operations teams, OpenAI fleet-health engineers, hardware engineering teams, and OEM vendors to identify, diagnose, and resolve hardware issues affecting production systems. Beyond day-to-day operational support, you will drive root cause investigations, reliability improvement initiatives, lifecycle management programs, and operational readiness efforts. You will help establish hardware maintenance standards, operational procedures, and best practices that scale across future OpenAI infrastructure deployments. The ideal candidate combines deep hands-on datacenter hardware expertise with strong troubleshooting, failure analysis, and cross-functional leadership skills. Candidates must be able to sit onsite at our

Position Overview: A Junior Research Analyst within the Diligent Market Intelligence function supports subject matter expertise in specialized research areas such as compensation, governance, activism, voting, and risk. Their main responsibilities include assisting in the design and management of data collection methodologies, overseeing third-party service provider workflows, and ensuring high-quality, timely data delivery. They are also expected to execute manual data collection from global sources, maintain strong quality assurance practices, and collaborate closely with Product and Engineering teams to ensure operational efficiency and accuracy. Additionally, Junior Research Analysts take ownership of specific daily and weekly tasks, contribute to ongoing projects, and play a key role in training service providers while keeping process documentation clear and up to date. The role requires strong numeracy, attention to detail, independent work habits, and a proactive approach to continuously improving research products and processes. Key Responsibilities: Proactive communication and management of outsourcer workload. Conduct data collection tasks to uphold the integrity of our database and keep it current. Execute systematic checks to identify data inaccuracies and operational inefficiencies as per predefined protocols. Provide regular updates and reports to the Vertical lead on progress and challenges. Take ownership of specific daily and weekly tasks, as well as ongoing projects within the assigned research vertically. Required Experience/Skills: Entry level Analytical approach and problem-solving attitude Strong written and verbal communication skills Ability to manage deadlines Ability to adapt to difficult workload demands, e.g., time/resource constraints Proficiency in Microsoft Office, especially Excel About Us Diligent is the AI leader in governance, risk and compliance (GRC) SaaS solutions, helping more than 1 million users and 70

Sr. Director of Commercial and Legal Affairs About Backblaze Backblaze is a public company that makes storing and using data astonishingly easy. When our founding team got together, they committed to helping people save their data. Today, the Backblaze Storage Cloud provides a foundational platform around the world for a broad community of developers, IT generalists, entrepreneurs, and individuals who seek the easy, affordable, trusted solutions we provide. We have managed to nurture a team-oriented culture with amazingly low turnover. Our approach is guided by honesty, transparency, and a commitment to doing the right thing. Our customers are happy, and so are our coworkers: in the most recent “Great Place to Work” survey, 97% of our team rated Backblaze as “a great place to work.” Check out what our employees are saying on Glassdoor! About the Role We are seeking a Sr. Director of Commercial and Legal Affairs to lead and oversee Backblaze’s commercial, privacy, and product legal functions. This is a people leader role that will serve as a strategic business partner across Sales, Product, Engineering, Security, and Compliance. The ideal candidate is a highly experienced commercial lawyer with a strong track record of drafting and negotiating complex technology transactions, including enterprise and strategic partnership deals. This role also requires fluency in privacy and data protection issues and hands-on experience advising product and engineering teams throughout the product lifecycle. This position will play a critical role in enabling scalable growth while thoughtfully managing legal and regulatory risk as Backblaze continues to expand globally. This role includes people management responsibilities and will lead, mentor, and develop attorney(s) and legal professional(s) supporting commercial, privacy, and product work. This role reports to the Head of Legal & Compliance and is fully remote (US-based). What You’ll Do Commercial Leadership and Deal Executi

Principal Targeting Analyst Target development for cyber operations, red-team engagements, and applied R&D Position Overview: Position: Principal Targeting Analyst Job Type: Full-time Location: Ft. Meade, MD (Hybrid) Clearance Requirements: US Citizen &TS/SCI Experience: 8+ years What You'll Do SIXGEN is seeking a Principal Targeting Analyst to build and lead an organic targeting and collection capability that strengthens our offensive cyber, red-team, and adversary-emulation missions. This is a hands-on technical leadership role for an analyst-engineer hybrid who enjoys solving hard collection problems, developing targets from a cold start, and turning operational experience into automated, mission-ready capability. As a Principal Targeting Analyst, you'll pair deep OSINT and managed-attribution tradecraft with professional foreign-language proficiency, applied AI engineering, and real software-development ability. You'll partner with operators, engineers, and program teams to deliver timely targeting and access intelligence, mature SIXGEN's collection methodologies and tooling, and mentor analysts as the capability grows. Whether you're developing a target for a critical customer mission, automating collection at scale, or shaping the technical direction of a new capability, your operational credibility and technical judgment will help drive mission success across the organization. Key Responsibilities Target Development and Key Operations Conduct end-to-end target development against threat actors, and adversary infrastructure — from initial requirement through finished, decision-ready intelligence. Direct collection across the surface, deep, and dark web, closed forums, encrypted messaging platforms, and regional ecosystems beyond the coverage of commercial data sources. Perform authorized threat-actor engagement and elicitation; track initial-access brokers, exploit sellers, and access markets relevant to mission objectives. Conduct

About Forma.ai: Forma.ai is a Series B startup that's revolutionizing how sales compensation is designed, managed and optimized. We handle billions in annual managed commissions for market leaders like Edmentum, Stryker, and Autodesk. Our growth has been fuelled by our passion for fundamentally changing and shaping how companies use sales intelligence to drive business strategy. We’re welcoming equally driven individuals who are excited about creating something big! Director, SPM Implementation About the Team The Customer Operations team partners with new and existing customers to implement and optimize the company’s platform, ensuring clients maximize the revenue-driving potential of their sales compensation programs. The team leads complex implementations, drives operational excellence, and continuously evolves Sales Performance Management (SPM) processes through data-driven insights and scalable platform solutions. As a Director of Implementation , you will lead the strategic direction of implementation and customer onboarding across a portfolio of enterprise customers. You will oversee implementation teams, guide architectural design of customer solutions, and collaborate closely with Product, Engineering, and Revenue teams to ensure the platform evolves in alignment with customer needs and business priorities. If you’re passionate about building high-performing teams, driving customer impact through data and technology, and shaping the future of sales operations , we’d love to hear from you. What You'll Be Doing Leadership & Strategy Define and lead the implementation strategy and operational framework for onboarding and scaling customer deployments. Build, mentor, and lead a high-performing implementation team , establishing best practices, processes, and standards for delivery excellence. Partner with executive leadership to align customer implementation strategy with company growth and product roadmap priorities . Establish KPI

Machine Learning Engineer We’re looking for a Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Experience: Multiple years of industry experience in Machine Learning, with at least 3 years dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native:

Machine Learning Engineer IV – (Computer Vision) We’re looking for a Staff/Senior Machine Learning Engineer with deep expertise in computer vision and biometrics to lead the design and scaling of face recognition systems in production. You’ll build and train models, and own ML systems end-to-end on AWS. The final job level for this role will be determined following the interview process. What You’ll Do Lead the design and development of computer vision systems for biometrics (face attributes, detection, quality, and recognition) Rigorous fairness analysis and benchmarking of biometric models across various datasets and operating conditions. Architect, train, and optimize models using PyTorch, Tensorflow, and/or JAX Own and evolve end-to-end ML pipelines, from data ingestion to deployment. Design automated pipelines (Airflow) for data ingestion and cleaning. You will be responsible for curating balanced training sets and generating synthetic data to address both quality and diversity gaps. Production Engineering: Own the path to production. Optimize models for low-latency inference (quantization, distillation, TensorRT/ONNX) and manage deployment on AWS. Mentor ML engineers, conduct code/design reviews, and drive technical best practices across the Computer Vision team. What We’re Looking For Strong industry experience in Machine Learning, dedicated to Biometrics or Face Analysis. Deep expertise in computer vision and biometrics, especially face recognition. Fairness & Ethics: You understand the sources of algorithmic bias in Computer Vision and have practical experience measuring and mitigating disparate impact. Strong Engineering: Expert proficiency in Python (both machine learning and vision libraries such as Pillow, OpenCV, PyTorch, etc). You write clean, modular, production-ready code. Systems Architecture: Experience designing end-to-end ML pipelines (Data to Train to Deploy) and working with workflow orchestrators like Airflow. Cloud Native: Hands-on exper

About the Team DoorDash Labs is an independent team within DoorDash. We explore robotics and automation to transform last mile logistics in the long term. If you have a passion for applying robotics solutions in a service used by millions of people, then we want to talk to you! About the Role We are hiring a Firmware Validation & Integration Engineer for our autonomy software team. This is a critical role to build robust and scalable validation for our firmware and systems to ensure reliability at every level. In this role, you will work with our electrical, firmware, and autonomy engineers to build the infrastructure and test suites required to validate the system. This includes designing and implementing our Hardware-in-the-Loop (HIL) simulation environments and automation frameworks from the ground up. You will report to the Autonomy Platform Lead on our Autonomy Platform Team at DoorDash Labs. We expect this role to be hybrid with some time in-office and some time remote. You’re excited about this opportunity because you will… Play an integral role on a small and focused team. Design and build Hardware-in-the-Loop (HIL) systems to simulate vehicle dynamics and sensor data for comprehensive firmware and system-level validation. Develop automated test infrastructure and software tools to exercise multiple embedded platforms throughout our robot system. Interface many layers of our control system including vehicle controls, power management, and motion control to ensure seamless system integration. Implement low-level test sequences and validation algorithms to safely stress-test vehicle components such as batteries, drive-train, and thermal management devices. Collaborate with cross-functional teams to identify edge cases and hardware-software corner cases that impact vehicle safety and performance. We’re excited about you because… BS/MS degree in Computer Science, Robotics, Electrical Engineering, or related technical field. 5+ years of experience in validati