Harnham
Director of Data Engineering
Location:
San Francisco or New York (Hybrid)
Compensation:
$300-350K base + Equity
A $3B+ Series E SaaS company at the forefront of AI-powered enterprise transformation is looking for a Director of Data Engineering to scale its Data Platform and Analytics Engineering functions. This is a rare opportunity to lead the next phase of data infrastructure, powering everything from LLM-based product experiences to executive analytics and real-time experimentation.
What You'll Lead: Data Platform Strategy:
Define the roadmap for scalable, cloud-native infrastructure-streaming, compute, and storage-including technologies like Apache Iceberg, Kafka, and Snowflake. Team & Technical Leadership:
Grow and mentor a high-performing data engineering team (2 10+), setting engineering standards and fostering technical excellence. Cross-Functional Collaboration:
Partner with ML, Security, Legal, and Product teams to enable AI/ML platforms, telemetry pipelines, and governance at scale. Systems at Scale:
Architect robust, real-time pipelines and petabyte-scale infrastructure with streaming pre-aggregations, observability, and cost efficiency. Operational Maturity:
Drive platform reliability and compliance-readiness as the company prepares for IPO-implementing best practices in governance, testing, and infrastructure as code. What We're Looking For
10+ years in data engineering, with 5+ years of engineering leadership Deep experience scaling data platforms in high-growth SaaS, infrastructure or AI-first environments Expert in Kafka, Apache Iceberg, Snowflake, dbt, and cloud infrastructure (AWS or GCP) Proven success supporting ML/AI platforms and structured/unstructured data needs Strong track record of partnering with legal and compliance to build IPO-ready systems A collaborative, technical leader who thrives in fast-paced, high-impact settings Why This Role
Lead the data engineering charter at one of the most innovative companies in enterprise AI Own systems that power product analytics, experimentation, personalization, and LLM workloads Work side-by-side with the C-suite and play a pivotal role in company-scale transformation
Location:
San Francisco or New York (Hybrid)
Compensation:
$300-350K base + Equity
A $3B+ Series E SaaS company at the forefront of AI-powered enterprise transformation is looking for a Director of Data Engineering to scale its Data Platform and Analytics Engineering functions. This is a rare opportunity to lead the next phase of data infrastructure, powering everything from LLM-based product experiences to executive analytics and real-time experimentation.
What You'll Lead: Data Platform Strategy:
Define the roadmap for scalable, cloud-native infrastructure-streaming, compute, and storage-including technologies like Apache Iceberg, Kafka, and Snowflake. Team & Technical Leadership:
Grow and mentor a high-performing data engineering team (2 10+), setting engineering standards and fostering technical excellence. Cross-Functional Collaboration:
Partner with ML, Security, Legal, and Product teams to enable AI/ML platforms, telemetry pipelines, and governance at scale. Systems at Scale:
Architect robust, real-time pipelines and petabyte-scale infrastructure with streaming pre-aggregations, observability, and cost efficiency. Operational Maturity:
Drive platform reliability and compliance-readiness as the company prepares for IPO-implementing best practices in governance, testing, and infrastructure as code. What We're Looking For
10+ years in data engineering, with 5+ years of engineering leadership Deep experience scaling data platforms in high-growth SaaS, infrastructure or AI-first environments Expert in Kafka, Apache Iceberg, Snowflake, dbt, and cloud infrastructure (AWS or GCP) Proven success supporting ML/AI platforms and structured/unstructured data needs Strong track record of partnering with legal and compliance to build IPO-ready systems A collaborative, technical leader who thrives in fast-paced, high-impact settings Why This Role
Lead the data engineering charter at one of the most innovative companies in enterprise AI Own systems that power product analytics, experimentation, personalization, and LLM workloads Work side-by-side with the C-suite and play a pivotal role in company-scale transformation