Software Engineer, Data Platform

Why consider this job opportunity:

• Competitive base salary range from $185,805 – $206,450
• Eligible for an annual variable bonus of cash and equity, between 10-20%
• Excellent benefits package including 401(K) match, adoption assistance, parental leave, and comprehensive medical/dental/vision coverage
• Opportunities for career advancement and professional development within a supportive work environment
• Flexible work-life balance in a casual work environment
• Recognition as a Great Place to Work with a focus on employee satisfaction and engagement

• Own architecture and implementation of key components of the modern data platform, ensuring production reliability and technical soundness
• Drive technical innovation by contributing to system design, implementation, and operational excellence
• Collaborate with peers to influence technology and architecture decisions, providing well‑reasoned perspectives
• Debug and resolve complex production issues, applying technical expertise to restore stability across services and systems
• Mentor and coach less experienced engineers, contributing to team growth and technical maturity

• Bachelor’s degree in Computer Science, Information Systems, or a closely related field; or equivalent work experience
• Minimum 5 years of software engineering experience, with hands‑on experience building and maintaining data platforms or distributed systems in cloud environments
• Strong knowledge of software engineering best practices, with practical experience in building data platforms
• Experience developing and supporting cloud‑native applications (AWS, Azure, or GCP), including containerized services (Docker, Kubernetes)
• Strong programming skills in one or more languages commonly used for platform engineering (e.g., Python, Java, Scala, Go)

• Advanced expertise in lakehouse technologies (Delta, Iceberg, Hudi), including performance tuning
• Hands‑on experience with workflow orchestration frameworks (Airflow, Dagster, Prefect)
• Strong background in CI/CD pipelines for platform services
• Familiarity with observability and SRE practices (SLAs/SLOs/SLIs, distributed tracing)
• Experience with performance tuning and cost optimization for large‑scale data platforms

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