Senior Software Engineer, Data Infrastructure

This is a fully remote position, open to applicants in Washington.

📋 Description

• Architect and develop essential components of Docker’s data platform while guiding its technical direction.

• Design and construct scalable data infrastructure utilizing Snowflake, AWS, Airflow, DBT, and Sigma.

• Create comprehensive data pipelines for both real-time and batch analytics across Docker’s product ecosystem.

• Assess data platform technologies, architectural frameworks, and engineering best practices.

• Establish benchmarks for data quality, testing, monitoring, and operational excellence.

• Construct high-throughput data systems that support a significant volume of user interactions.

• Develop DBT data transformations and models for analytics and business intelligence purposes.

• Create and maintain workflows for orchestration using Apache Airflow.

• Enhance Snowflake's performance and cost-effectiveness.

• Develop data APIs and services to facilitate self-service analytics and downstream integrations.

• Translate business and product analytics requirements into actionable technical solutions.

• Collaborate with Data Scientists and Analysts on analytics, machine learning, and business intelligence capabilities.

• Deliver precise reporting and operational dashboards in collaboration with Finance, Sales, and Marketing teams.

• Support customer-facing analytics and embedded reporting initiatives.

• Collaborate with Security and Compliance teams on data governance and regulatory adherence.

• Ensure reliability, monitoring, alerting, and incident response for the components you own.

• Implement data quality validations and automated testing for pipelines and transformations.

• Establish disaster recovery and business continuity protocols.

• Troubleshoot and resolve intricate issues affecting data availability and accuracy.

• Mentor engineers on system architecture, technical execution, and data engineering methodologies.

• Conduct technical design evaluations and provide feedback on architectural decisions.

• Share expertise through documentation, tech talks, and cross-team collaborations.

• Engage in hiring processes and technical evaluations for data engineering positions.

⛳️ Requirements

• 6+ years of experience in software engineering, with at least 3 years focused on data engineering.

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent hands-on experience.

• Extensive experience with Snowflake, including SQL optimization, performance enhancements, and cost management.

• Proficient in using DBT for data modeling, transformation, and production-scale testing.

• Experience in orchestrating workflows and pipelines using Apache Airflow.

• Familiarity with Sigma or similar modern BI platforms for self-service analytics.

• Practical experience with AWS data services (S3, Redshift, EMR, Glue, Lambda, Kinesis).

• Proficient in Python and SQL for applications in data engineering.

• Experience with Infrastructure-as-Code, CI/CD pipelines, and contemporary DevOps practices.

• Proven track record in designing and building large-scale distributed data systems.

• Strong understanding of data warehousing, dimensional modeling, and analytics architectures.

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

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

• Demonstrated success in optimizing performance and costs for cloud data infrastructures.

• Ability to make informed technical decisions based on sound engineering judgment.

• Experience mentoring engineers and leading technical projects without direct management authority.

• Excellent written and verbal communication skills, adaptable to both technical and non-technical audiences.

• Proven capability to collaborate effectively with Product, Business, and Engineering teams.

• Visa sponsorship evaluated on a case-by-case basis depending on business needs.

• Preferred: Experience in high-growth technology companies, especially in developer tools or infrastructure software.

• Preferred: Background with container technologies, Kubernetes, or cloud-native development.

• Preferred: Knowledge of machine learning platforms and MLOps methodologies.

• Preferred: Experience with GCP or Azure and multi-cloud data strategies.

• Preferred: Familiarity with data catalog tools, metadata management, and data lineage systems.

• Preferred: Advanced degree in Computer Science, Data Engineering, or a related technical discipline.

• Preferred: Experience with customer-facing analytics and embedded reporting solutions.

• Preferred: Knowledge of financial data systems and revenue analytics.

🏝️ Benefits

• Remote-first design; work from home, with offices in Seattle and Paris for connection and collaboration.

• Flexible work schedule.

• Generous paid time off (PTO).

• Designated quarterly Whaleness Days.

• Scheduled end-of-year Whaleness break.

• Support for home office setup.

• Technology stipend equivalent to US$100 net per month.

• Annual learning and development stipend for conferences, courses, certifications, and ongoing education.

• 16 weeks of paid parental leave after six months of employment.

• Equity offered to all full-time employees.

• Medical benefits provided.

• Retirement benefits available.

• Paid holidays.

• Docker merchandise.