Senior Software Engineer (Data Infrastructure)

Location: Remote in the United States; offices available in Seattle and Paris for connection and collaboration.

Salary: $160,900–$260,700 annually plus equity in the United States.

Company

hirify.global builds developer tools and infrastructure used to build, share, and run applications, including hirify.global Desktop, hirify.global Hub, and hirify.global Scout.

What you will do

• Architect and implement scalable data platform components using Snowflake, AWS, Apache Airflow, DBT, and Sigma.
• Build high-throughput real-time and batch data pipelines, transformations, models, APIs, and self-service analytics services.
• Optimize Snowflake performance, reliability, and infrastructure costs while establishing data quality, testing, monitoring, and operational standards.
• Translate analytics requirements into technical solutions and collaborate with Product, Engineering, Sales, Marketing, Finance, Data Science, and Analytics teams.
• Implement monitoring, alerting, incident response, disaster recovery, and business continuity for critical data systems.
• Mentor engineers, lead design reviews, guide technical direction, document systems, and participate in hiring and technical assessments.

Requirements

• 6+ years of software engineering experience, including 3+ years focused on data engineering.
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• Strong production experience with Snowflake, including SQL tuning, performance optimization, and cost management.
• Proficiency with DBT, Apache Airflow, Python, SQL, AWS data services, Infrastructure-as-Code, CI/CD, and modern DevOps practices.
• Experience designing large-scale distributed data systems, data warehouses, dimensional models, stream processing, event-driven architectures, and real-time systems.
• Understanding of data governance, security, privacy frameworks, reliability engineering, and cloud infrastructure optimization.

Nice to have

• Experience at high-growth technology companies, especially in developer tools or infrastructure software.
• Background with container technologies, Kubernetes, or cloud-native development.
• Knowledge of machine learning platforms, MLOps, additional cloud platforms, data catalogs, metadata management, or data lineage.
• Experience with customer-facing analytics, embedded reporting, financial data systems, or revenue analytics.
• Advanced degree in Computer Science, Data Engineering, or a related technical field.

Culture & Benefits

• Remote-first work with flexible scheduling and home office support.
• Generous paid time off, quarterly Whaleness Days, and an end-of-year Whaleness break.
• US$100 net monthly technology stipend and an annual learning and development stipend.
• 16 weeks of paid parental leave after six months of employment.
• Equity for all full-time employees, with medical, retirement, and paid holiday benefits varying by country.

Hiring process

• Technical assessments and interviews are part of the hiring process.
• AI-assisted hiring tools may be used.
• Interview recordings are optional and require explicit consent.