Data Engineer (Databricks/Spark)

Location: San Francisco, United States; in-person work 5 days per week in the office

Estimated base salary: $200K–$400K per year

Company

hirify.global is building an AI-native revenue platform that unifies CRM, sequencing, call recording, enrichment, and pipeline management in a single enterprise software system.

What you will do

• Build, deploy, and operate production Spark data pipelines on Databricks.
• Partner with product teams to translate analytics needs into pipeline requirements, including data quality and freshness expectations.
• Set up monitoring and observability to measure pipeline reliability.
• Diagnose and resolve performance and cost issues at their root cause.
• Recommend pragmatic standards for operating pipelines as the data and platform scale.

Requirements

• Hands-on experience building, deploying, and maintaining production Spark pipelines.
• Deep understanding of clustering, shuffles, join strategies, and batch-versus-stream processing tradeoffs.
• Experience with reliability, monitoring, and observability, including diagnosing pipeline failures or bottlenecks.
• Strong SQL and basic programming skills in any language.
• Comfort working as an individual contributor directly with product teams and through ambiguity.
• Experience level of approximately 2–6 years.

Nice to have

• Familiarity with the Databricks ecosystem.
• Experience with streaming pipelines and logical replication, such as replicating Postgres into Databricks.
• Experience building RAG pipelines.
• AWS infrastructure experience.
• Platform administration experience, including roles, permissions, access controls, and visibility management.

Culture & Benefits

• High-autonomy, high-pace environment.
• Hands-on individual contributor role with direct collaboration across product and engineering.
• Opportunity to scale core systems and build new features from 0 to 1.
• In-person collaboration with the full team in the San Francisco office.