Senior Software Engineer, Data Infrastructure

Translate business and product analytics requirements into technical solutions

Collaborate with Data Scientists and Analysts to enable advanced analytics, ML, and BI capabilities

Work with Finance, Sales, and Marketing teams to deliver accurate reporting and operational dashboards

Support customer-facing analytics initiatives and embedded reporting capabilities

Partner with Security and Compliance to ensure data governance and regulatory compliance

Ensure system reliability, monitoring, alerting, and incident response for owned components

Implement data quality checks and automated testing for data pipelines and transformations

Optimize performance and manage infrastructure costs across the data platform

Establish disaster recovery and business continuity procedures for critical data systems

Lead troubleshooting and resolution of complex technical issues affecting data availability and accuracy

Mentor engineers on system design, technical execution, and data engineering best practices

Conduct technical design reviews and provide actionable feedback on software architecture

Contribute to knowledge sharing through documentation, tech talks, and cross-team collaboration

Model engineering excellence practices within the data team

Participate in hiring and technical assessment processes for data engineering roles

6+ years of software engineering experience, with 3+ years focused on data engineering

Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience

Strong experience with Snowflake, including SQL tuning, performance optimization, and cost management

Proficiency with DBT for data modeling, transformation, and testing at production scale

Experience orchestrating workflows and pipelines with Apache Airflow

Experience using Sigma or similar modern BI platforms for self-service analytics

Production experience with AWS data services (S3, Redshift, EMR, Glue, Lambda, Kinesis)

Proficiency in Python and SQL for data engineering applications

Experience with Infrastructure-as-Code, CI/CD pipelines, and modern DevOps practices

Track record of designing and building large-scale distributed data systems

Solid understanding of data warehousing, dimensional modeling, and analytics architectures

Experience with stream processing, event-driven architectures, and real-time data systems

Understanding of data governance, security standards, and privacy frameworks (e.g., GDPR, CCPA)

Proven track record optimizing performance and cost for cloud data infrastructure

Ability to guide technical choices through sound engineering judgment

Experience mentoring engineers and leading technical projects without direct management authority

Clear written and verbal communication skills, tailored to technical and non-technical stakeholders

Proven ability to collaborate effectively with Product, Business, and Engineering partners

Experience at high-growth technology companies, particularly in developer tools or infrastructure software

Background with container technologies, Kubernetes, or cloud-native development

Knowledge of machine learning platforms and MLOps practices

Experience with additional cloud platforms such as GCP or Azure and multi-cloud data strategies

Familiarity with modern data catalog tools, metadata management, and data lineage systems

Advanced degree in Computer Science, Data Engineering, or a related technical field

Experience with customer-facing analytics and embedded reporting solutions

Knowledge of financial data systems and revenue analytics

Timely delivery of scalable data systems supporting company-wide analytics needs

System reliability and performance metrics meeting enterprise SLA requirements

Cost optimization achievements for data infrastructure without sacrificing performance

Effective mentorship demonstrated through team skill growth and knowledge sharing

Cross-functional stakeholder satisfaction with data platform capabilities and reliability

Adoption of data engineering best practices and technical standards across the team

As a Senior Software Engineer on our Data Infrastructure team, you will build the foundation powering Docker's product analytics and business intelligence.

You will design and implement systems that allow teams across the company to make data-informed decisions while expanding Docker's enterprise capabilities.

You will solve challenging technical problems at scale, expand your technical leadership, and mentor fellow engineers.

Your work will enable millions of developers to build software efficiently through data-driven insights.

Docker considers visa sponsorship on a case-by-case basis based on business needs.

United States: $160,900 – $260,700 + equity

Open vacancy: This posting is for an existing open role.

AI in hiring: Docker may use AI-assisted tools during our recruiting process.

Interview recordings: Candidates will be invited to opt in to interview recordings to support interviewer calibration and consistent evaluations.

Recordings are optional and require explicit consent.

Remote-first by design – Work from your home, with offices in Seattle and Paris for connection and collaboration.

Flexibility that fits your life – We trust you to manage your schedule while delivering great work.

Time to recharge – Generous PTO, designated quarterly Whaleness Days, and a designated end-of-year Whaleness break.

Home office support – Set up your workspace for comfort and success.

Technology stipend – Equivalent to US$100 net per month to help support your work.

Learning & development – Annual stipend for conferences, courses, certifications, and continued learning.

Parental leave – 16 weeks of paid parental leave after six months of employment.

Equity for all full-time employees – Share in Docker's long-term success as we continue to grow.

Comprehensive benefits – Medical, retirement, and paid holidays vary by country.

Docker swag – Because representing the whale never gets old.

Docker is proud to be an equal opportunity employer.

We are committed to building a team that reflects a broad range of backgrounds, experiences, and perspectives.

We believe diverse teams build better products, make better decisions, and better serve our global community.

#LI-REMOTE