Software Engineer, Data Engineering (AI)

TL;DR

Senior Software Engineer (Data Engineering): Architecting and developing large-scale data platforms and pipelines for an AI productivity platform with an accent on scalability, security, and efficiency across data engineering systems. Focus on designing robust solutions for real-time and ETL data processing, cloud infrastructure, and data lakes while mentoring engineers and setting strategic direction.

Location: Hybrid (Must be based in San Francisco or New York City)

Salary: $225,000–$275,000 (USD)

Company

hirify.global is part of Superhuman, an AI productivity platform empowering over 40 million people and 50,000 organizations to eliminate busywork and focus on what matters.

What you will do

• Architect and lead development of large-scale systems for data pipelines and data lakes handling billions of daily events.
• Design and implement solutions ensuring data is available, secure, and scalable across the platform, enabling real-time and batch processing.
• Make high-level architectural decisions about system design, technology choices, and platform evolution for long-term sustainability.
• Collaborate with product teams, data engineers, back-end developers, and ML engineers to build tools and frameworks for analytics and product features.
• Work with business stakeholders to build high-impact data products enabling business-critical features, research, and experimentation.
• Mentor engineers across back-end infrastructure and data engineering disciplines, fostering technical excellence.

Requirements

• 10+ years of experience in large-scale distributed computing systems, with expertise in both data engineering and data modeling.
• 5+ years of experience managing live production environments, including high-load or data-intensive workflows.
• Expert in SQL and proficient in technologies like Spark, Kafka, Terraform, and in at least one programming language (e.g., Python, Scala, or Java).
• Strong knowledge of ETL/ELT design patterns, orchestration tools (e.g., Airflow, dbt, Dagster), and data quality frameworks.
• Ability to design scalable, secure, and maintainable data models and architectures, with an understanding of data governance and privacy regulations (GDPR/CCPA).
• Hands-on experience with modern data storage technologies (e.g., Delta Lake, Snowflake, BigQuery, Redshift).
• Must be based in San Francisco or New York City.

Culture & Benefits

• Competitive pay along with excellent health care (medical, dental, vision, mental health, and fertility benefits).
• Disability and life insurance options, with 401(k) matching.
• 20 days of paid time off, 12 paid holidays, two floating holidays, and flexible sick time.
• Generous stipends for caregiving, pet care, wellness, and home office.
• Annual professional development budget and opportunities for continuous learning.