At Docker, we make app development easier so developers can focus on what matters. Our remote-first team spans the globe, united by a passion for innovation and great developer experiences. With over 20 million monthly users and 20 billion image pulls, Docker is the #1 tool for building, sharing, and running apps—trusted by startups and Fortune 100s alike. We’re growing fast and just getting started. Come join us for a whale of a ride!Docker is seeking a Staff Software Engineer to join our Data Infrastructure team and drive the technical evolution of data systems that power analytics across the entire company. As Docker continues to scale with millions of developers and thousands of enterprise customers globally, we need a senior technical leader who can design, build, and launch scalable data infrastructure that enables data-driven decision making across Product, Engineering, Sales, Marketing, Finance, and Executive teams.This is a hands-on technical leadership role combining deep individual contribution with strategic thinking and mentorship responsibilities. You'll be responsible for architecting and implementing robust data systems and processes that support Docker's analytic needs while establishing technical standards and best practices for the data organization. You'll work closely with cross-functional teams to understand requirements and deliver data solutions that drive business outcomes.Success in this role requires expert-level technical skills in modern data platforms, strong system design capabilities, and the ability to influence technical direction while mentoring and developing other engineers. You'll play a critical role in scaling Docker's data capabilities as we continue to expand our product portfolio and serve enterprise customers worldwide. ResponsibilitiesTechnical Strategy & Architecture LeadershipDefine and drive the technical strategy for Docker's data platform architecture, establishing long-term vision for scalable data systemsLead design and implementation of highly scalable data infrastructure leveraging Snowflake, AWS, Airflow, DBT, and SigmaArchitect end-to-end data pipelines supporting real-time and batch analytics across Docker's product ecosystemDrive technical decision-making around data platform technologies, architectural patterns, and engineering best practicesEstablish technical standards for data quality, testing, monitoring, and operational excellenceHands-On Engineering & System DevelopmentDesign and build robust, scalable data systems that process petabytes of data and support millions of user interactionsImplement complex data transformations and modeling using DBT for analytics and business intelligence use casesDevelop and maintain sophisticated data orchestration workflows using Apache AirflowOptimize Snowflake performance and cost efficiency while ensuring reliability and scalabilityBuild data APIs and services that enable self-service analytics and integration with downstream systemsCross-Functional Collaboration & Requirements EngineeringPartner with Product, Engineering, and Business teams to understand analytics requirements and translate them into technical solutionsCollaborate with Data Scientists and Analysts to enable advanced analytics, machine learning, and business intelligence capabilitiesWork with Finance, Sales, and Marketing teams to deliver accurate reporting and operational dashboardsSupport customer-facing analytics initiatives and embedded reporting capabilitiesEngage with Security and Compliance teams to ensure data governance and regulatory requirements are metTechnical Operations & ReliabilityOwn operational excellence for critical data systems including monitoring, alerting, and incident responseImplement comprehensive data quality frameworks and automated testing for data pipelines and transformationsDrive performance optimization and cost management initiatives across the data platformEstablish disaster recovery and business continuity procedures for business-critical data systemsLead troubleshooting and resolution of complex technical issues affecting data availability and accuracyMentorship & Technical LeadershipMentor junior and mid-level engineers on technical skills, system design, and data engineering best practicesConduct technical design reviews and provide guidance on architectural decisionsDrive knowledge sharing initiatives including documentation, tech talks, and cross-team collaborationEstablish and promote engineering excellence practices across the data organizationContribute to hiring and technical assessment processes for data engineering rolesRequired QualificationsTechnical Expertise8+ years of software engineering experience with 3+ years focused on data engineering and analytics systemsExpert-level experience with Snowflake including advanced SQL, performance optimization, and cost managementDeep proficiency in DBT for data modeling, transformation, and testing with experience in large-scale implementationsStrong expertise with Apache Airflow for complex workflow orchestration and pipeline managementHands-on experience with Sigma or similar modern BI platforms for self-service analyticsExtensive AWS experience including data services (S3, Redshift, EMR, Glue, Lambda, Kinesis) and infrastructure managementProficiency in Python, SQL, and other programming languages commonly used in data engineeringExperience with infrastructure-as-code, CI/CD practices, and modern DevOps toolsBachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experienceSystem Design & ArchitectureProven track record designing and implementing large-scale distributed data systemsDeep understanding of data warehousing concepts, dimensional modeling, and analytics architecturesExperience with stream processing, event-driven architectures, and real-time data systemsKnowledge of data governance, security frameworks, and compliance requirements (GDPR, CCPA)Strong background in performance optimization and cost management for cloud data platformsLeadership & CollaborationDemonstrated ability to drive technical strategy and influence engineering decisions across teamsExperience mentoring engineers and leading technical initiatives without direct management authorityExcellent communication skills with ability to explain complex technical concepts to diverse audiencesTrack record of successful cross-functional collaboration with Product, Business, and Executive stakeholdersExperience establishing technical standards and driving adoption across engineering organizationsPreferred QualificationsExperience at high-growth technology companies, particularly in developer tools or infrastructure softwareBackground with container technologies, Kubernetes, or cloud-native developmentKnowledge of machine learning platforms and MLOps practicesExperience with additional cloud platforms (GCP, Azure) and multi-cloud data strategiesFamiliarity with modern data catalog tools, metadata management, and data lineage systemsAdvanced degree in Computer Science, Data Engineering, or related technical fieldExperience with customer-facing analytics and embedded reporting solutionsKnowledge of financial data systems and revenue analyticsKey Success MetricsSuccessful design and delivery of scalable data systems supporting company-wide analytics needsSystem reliability and performance metrics meeting enterprise SLA requirementsCost optimization achievements for data infrastructure while maintaining performanceTechnical mentorship effectiveness measured by team growth and knowledge transferCross-functional stakeholder satisfaction with data platform capabilities and reliabilityContribution to data engineering best practices and technical standards adoptionImpact You'll MakeAs a Staff Software Engineer in our Data group, you'll be instrumental in building the data foundation that powers Docker's product innovation and business intelligence. You'll architect and implement systems that enable teams across Docker to make data-driven decisions while creating analytics capabilities that differentiate our products in the market. Your technical leadership will be critical to scaling Docker's data infrastructure as we continue to expand our product portfolio and serve enterprise customers globally.You'll have the opportunity to work on challenging technical problems at scale while directly influencing Docker's data strategy and mentoring the next generation of data engineers. Your contributions will enable millions of developers to build better software through the insights and capabilities your data systems provide.Docker considers sponsorship on a case-by-case basis based on business needs.We use Covey as part of our hiring and / or promotional process for jobs in NYC and certain features may qualify it as an AEDT. As part of the evaluation process we provide Covey with job requirements and candidate submitted applications. We began using Covey Scout for Inbound on April 13, 2024.Please see the independent bias audit report covering our use of Covey here.PerksFreedom & flexibility; fit your work around your lifeDesignated quarterly Whaleness Days plus end of year Whaleness breakHome office setup; we want you comfortable while you work16 weeks of paid Parental leaveTechnology stipend equivalent to $100 net/monthPTO plan that encourages you to take time to do the things you enjoyTraining stipend for conferences, courses and classesEquity; we are a growing start-up and want all employees to have a share in the success of the companyDocker SwagMedical benefits, retirement and holidays vary by countryRemote-first culture, with offices in Seattle and ParisDocker embraces diversity and equal opportunity. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better our company will be.#LI-REMOTE