TL;DR

Senior Software Engineer (Data Engineering): Architecting and leading the development of large-scale systems for data pipelines and data lakes, handling billions of daily events, with an accent on scalability, security, and efficiency. Focus on designing and implementing robust real-time & ETL data pipelines, cloud infrastructure, and back-end services to empower product features and data-driven decision-making.

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

Salary: $225,000–$275,000 (USD)

Company

%hirify_global% is an AI productivity platform empowering over 40 million people and 50,000 organizations with writing assistance, collaborative workspaces, inbox management, and proactive AI assistance.

What you will do

Architect and lead development of large-scale data systems for pipelines and data lakes.
Design and implement solutions for data availability, security, and scalability, enabling real-time and batch processing.
Make high-level architectural decisions on system design and technology choices.
Collaborate with product, data, back-end, and ML engineers to build data tools and frameworks.
Work with business stakeholders to build high-impact data products for critical features, research, and experimentation.
Mentor engineers across back-end infrastructure and data engineering disciplines.

Requirements

10+ years of experience in large-scale distributed computing systems with expertise in data engineering and data modeling.
5+ years of experience managing live production environments, including high-load systems or data-intensive workflows.
Expert in SQL and proficient in technologies like Spark, Kafka, Terraform, and a data engineering 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, and understanding of data governance and privacy regulations (GDPR/CCPA).
Hands-on experience with modern data storage technologies (e.g., Delta Lake, Snowflake, BigQuery, Redshift).
Excellent communicator and collaborator, capable of working across diverse teams.

Culture & Benefits

Competitive pay and comprehensive benefits package.
Excellent health care (medical, dental, vision, mental health, and fertility benefits).
401(k) and RRSP matching.
Paid parental leave, 20 days of paid time off, 12 paid holidays, and flexible sick time.
Generous stipends for caregiving, pet care, wellness, and home office.
Annual professional development budget and opportunities.
Hybrid working model fostering trust, innovation, and strong team culture.

Software Engineer, Data Engineering