Database Engineer

🏢 Summary: The role involves building and scaling structured and unstructured database platforms that power distributed systems and machine learning infrastructure. You will design, optimize, and operate high-availability database systems in cloud environments, ensuring performance, scalability, and security. The position includes architectural ownership, cross-functional collaboration, and improving database standards and reliability at scale. 🗂️ Requirements: 5+ years experience as Database Engineer, Experience building real-time distributed systems, Experience designing and self-hosting databases on public cloud platforms, Strong expertise in database design, architecture, optimization, and tuning, Experience with SQL optimization, indexing, sharding, replication, Experience implementing backup and restore strategies meeting RTO goals, Proficiency in at least one programming language (Typescript, Python, Go, Java, or C++), Experience with containerization and Infrastructure-as-Code tools 📃 Skills: MongoDB, Postgres, MySQL, DynamoDB, Redis, SQL, Typescript, Python, Go, Java, C++, Docker, Kubernetes, Terraform, AWS, Datadog, ElasticSearch, Snowflake, Databricks 🏢 Description: Scale is powering this generative AI wave by providing the data and infrastructure for companies to build large-scale foundation models. AI is rapidly changing the world, and Scale is growing to meet that rapid demand. Our customers include OpenAI, Microsoft, Adept, Stability AI and many more major players in this space! The Platform team is responsible for building the core abstractions and infrastructure on which the products can be built and iterated rapidly. The team owns how data flows throughout the Scale platform. We’re looking for a database engineer with deep experience building and scaling both structured and unstructured database platforms supporting distributed systems, data-intensive applications, and machine learning infrastructure. You have a growth mindset and are comfortable learning new technologies. You will: Build and mature database foundations for Scale, leveraging industry-standard platforms. Collaborate with stakeholders across the organization, such as software developers, platform engineers, machine learning scientists, customer operations, etc. Own services or systems and define their long-term health goals, while also improving the health of surrounding components. Mentor other engineers and become deeply involved in architectural design and database best-practices. Improve our high engineering standards, tooling, and process. Work directly with our engineering and sales teams to create backend database solutions to meet their challenging data and security needs. Work with our Security Team on security compliance, pen tests and mitigations that improve security across Scale. Build systems capable of handling millions of frames of data every day, making it available to both our workforce and our internal teams with high availability. This role could be a fit if you have: 5+ years of industry experience as a database engineer post graduation. Engineering experience with building real-time and distributed system architecture. Experience designing and self hosting databases on industry standard public cloud platforms Deep familiarity with design, architecture, optimization, and tuning multiple database platforms such as MongoDB, Postgres, MySQL, DynamoDB, Redis Deep familiarity with SQL query optimization, database indexing, scalability (partitioning/sharding), and replication Experience developing and optimizing backup and restore functionality to meet RTO goals Intermediate experience in at least one coding language: Typescript, Python, Go, Java, C++ (note that we are mostly language-agnostic and are open to using whatever is the best tech for the problem at hand). Experience working with Docker, Kubernetes, and Infra-as-Code (e.g. Terraform); bonus points for experience supporting GPU/ML workloads. Nice to haves: Prior startup experience to help us grow responsibly. Experience with AWS, Datadog, ElasticSearch Experience with cloud-based data warehouse solutions like Snowflake or Databricks. Experience with cost optimization strategies and techniques for database platforms. Experience developing and designing intermediary data abstraction layers. Mentored and grown members of your team or been a tech lead on large projects. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position, determined by work location and additional factors, including job-related skills, experience, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You’ll also receive benefits including, but not limited to: Comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend.Please reference the job posting's subtitle for where this position will be located. For pay transparency purposes, the base salary range for this full-time position in the locations of San Francisco, New York, Seattle is:$162,400—$203,000 USDPLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status. We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision. PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

🏢 Summary: Software engineering role in the Data Platform team focused on building and maintaining data-driven applications, including AI-powered data access tools. The position involves developing scalable data and metadata solutions and contributing to high-impact projects across the organization. You will work across legacy and greenfield systems while leveraging modern AI-assisted development practices. 🗂️ Requirements: 3+ years of software engineering experience, Proficiency in Python, Proficiency in SQL 📃 Skills: Python, SQL, Kubernetes, Kafka, Trino, Grafana, Prometheus, CloudWatch, AWS, Copilot, Claude, Codex, AI, Cloud, Data, Metadata 🏢 Description: Join the Data Platform team to build and maintain data-driven applications, including AI-powered data access tools. Work on a mix of legacy, improved, and greenfield projects with firm-wide impact. What you’ll do: Develop and enhance solutions for data and metadata access Build reliable, scalable applications and operational processes Experiment with AI-assisted development tools and share best practices Collaborate in a distributed team, taking ownership of impactful projects What we’re looking for: 3+ years in software engineering, Python and SQL experience Experience with data systems, cloud technologies, or AI-assisted tools is a plus Product-oriented mindset, comfortable navigating ambiguity, and impact-focused Nice to have: Experience with Kubernetes, Kafka, or federated query engines (e.g., Trino) Familiarity with monitoring/observability tools like Grafana, Prometheus, CloudWatch Experience with AWS or other cloud platforms Hands-on experience with AI coding assistants (Copilot, Claude Code, Codex, etc.) Why join: High-visibility, high-impact role across the firm Shape AI-driven development and data access practices Work on cutting-edge tech in institutional finance Collaborative culture with competitive compensation

🏢 Summary: Design and scale high-throughput data pipelines on cloud platforms to support advanced analytics and AI-driven products. The role focuses on building distributed data architectures in AWS and Databricks, ensuring performance, governance, and data quality. You will collaborate with AI/ML teams to deliver scalable, production-grade data solutions. 🗂️ Requirements: 3+ years of data engineering experience, Strong Python programming skills, Experience with Spark or Scala, Experience building distributed data pipelines in cloud environments, Knowledge of data modeling and data warehousing principles, Bachelor’s or Master’s degree in Computer Science or Engineering 📃 Skills: Python, Spark, Scala, AWS, Glue, EMR, Fargate, StepFunctions, Databricks, SQL, APIs, GenAI, GraphDB 🏢 Description: Data Engineer – Cloud & AI Platforms We’re looking for a Data Engineer to design and scale high-throughput data pipelines supporting advanced analytics and AI-driven products. What You’ll Do Architect and maintain distributed data pipelines in Databricks and AWS (Glue, EMR, Fargate, Step Functions) Ingest and process large volumes of structured and unstructured data (internal, market, third-party, alternative sources) Collaborate with AI/ML and engineering teams to design scalable data architectures and APIs Optimize performance and cost using Spark and cloud-native best practices Implement data governance, privacy, lineage, and access controls Build automated validation, monitoring, and data quality frameworks Evaluate emerging GenAI and data tooling to enhance platform capabilities What You Bring 3+ years of experience in data engineering Strong Python and experience with Spark or Scala Proven experience building distributed pipelines in cloud environments Solid understanding of data modeling, architecture, and warehousing principles Innovative problem-solving mindset Bachelor’s or Master’s degree in Computer Science or Engineering Nice to have: Experience with graph databases.

🏢 Summary: Leadership role to build and scale a 0→1 ML/AI platform enabling large-scale model training and inference across the organization. The position drives technical vision, roadmap, and organizational structure while overseeing multiple teams and managers. It covers the full AI lifecycle, from training and serving to deployment and monitoring, using open-source tooling. 🗂️ Requirements: Experience building 0→1 ML/AI platforms, Hands-on experience with open-source ML infrastructure (e.g., Ray, AnyScale), Strong technical background in large-scale training and inference systems, Experience managing managers and leading multiple engineering teams, Proven record of delivering production-grade AI systems, Experience defining technical vision and roadmap for AI platforms, Experience supporting full AI lifecycle: training, serving, deployment, monitoring 📃 Skills: Python, Ray, AnyScale, ML, AI, OpenSource, Training, Inference, Deployment, Monitoring, Infrastructure, Platforms 🏢 Description: The AI platform is responsible for all AI infrastructure across Datadog. Our mission is to provide tools and platforms that enable data scientists and engineers to conduct large-scale training and inference with ease. We support products such as Bits AI, LLMObs and all our AI research. You’ll join a new and fast growing team that is critical to the future of Datadog. You will support building and scaling the team, help define our technical vision and help shape the roadmap. You will manage other managers and help define the future structure of our organization, participating in the recruitment of the future managers and ICs of the department. You’ll work closely with partner teams in the AI platform organization ensuring a seamless AI development cycle. You’ll also partner with the Applied AI org, product engineering teams, and Datadog infrastructure & tooling teams to build out systems from the ground up. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Lead a fast-growing organization around 20 people across 2 teams soon to be 3. You will define the roadmap for your scope and work with ICs and managers to establish the technical direction Collaborate with the engineering team and product manager to define the future of the roadmap Create a strong organizational culture centered around our engineering standards and customer- focused approach Support the whole lifecycle of AI development, including model training, serving, deployment and monitoring Who You Are: You’ve led teams that have built 0 to 1 ML/AI Platforms, with an emphasis on Open Source Tooling (i.e. Ray / AnyScale), versus pure out-of-the-box solutions. An experienced engineer and team player with strong technical skills to influence the technical direction of your teams A people leader with strong interpersonal skills, who has built and led high-performing software engineering teams, including managing managers Interested in working on an early stage project with many challenges to solve and a fast iteration cycle. You bring a strong bias for delivery and make impact through ambiguity. You have a track record of delivering high-quality software on schedule and collaborating closely with product partners. Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply. Benefits and Growth: New hire stock equity (RSUs) and employee stock purchase plan (ESPP) Continuous professional development, product training, and career pathing Intradepartmental mentor and buddy program for in-house networking An inclusive company culture, ability to join our Community Guilds (Datadog employee resource groups) Access to Inclusion Talks, our Internal panel discussions Free, global mental health benefits for employees and dependents age 6+ Competitive global benefits Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog. #LI-HybridDatadog offers a competitive salary and equity package, and may include variable compensation. Actual compensation is based on factors such as the candidate's skills, qualifications, and experience. In addition, Datadog offers a wide range of best in class, comprehensive and inclusive employee benefits for this role including healthcare, dental, parental planning, and mental health benefits, a 401(k) plan and match, paid time off, fitness reimbursements, and a discounted employee stock purchase plan.The reasonably estimated yearly salary for this role at Datadog is:$234,000—$300,000 USD About Datadog: Datadog (NASDAQ: DDOG) is a global SaaS business, delivering a rare combination of growth and profitability. We are on a mission to break down silos and solve complexity in the cloud age by enabling digital transformation, cloud migration, and infrastructure monitoring of our customers’ entire technology stacks. Built by engineers, for engineers, Datadog is used by organizations of all sizes across a wide range of industries. Together, we champion professional development, diversity of thought, innovation, and work excellence to empower continuous growth. Join the pack and become part of a collaborative, pragmatic, and thoughtful people-first community where we solve tough problems, take smart risks, and celebrate one another. Learn more about #DatadogLife on Instagram, LinkedIn, and Datadog Learning Center. Equal Opportunity at Datadog: Datadog is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and other characteristics protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. Here are our Candidate Legal Notices for your reference. Datadog endeavors to make our Careers Page accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please complete this form. This form is for accommodation requests only and cannot be used to inquire about the status of applications. Privacy and AI Guidelines: Any information you submit to Datadog as part of your application will be processed in accordance with Datadog’s Applicant and Candidate Privacy Notice. For information on our AI policy, please visit Interviewing at Datadog AI Guidelines.