Senior Data Infrastructure Engineer

Harrison Clarke; San Francisco (CA); On-site; USD 130,000 - 160,000; Full time

Job summary

Harrison Clarke is seeking a Senior Data Infrastructure Engineer for a high-growth technology startup in San Francisco. The role involves building and evolving data infrastructure to support analytics, product development, and business intelligence.

The ideal candidate has over 5 years of experience in data engineering, a strong background in cloud platforms, and proficiency in programming languages like Python or Scala. Join a dynamic team and play a key role in scaling data capabilities.

Qualifications

• 5+ years of experience in data engineering or data infrastructure roles.
• Strong background in distributed systems and cloud platforms (AWS, GCP, or Azure).
• Hands‑on experience with tools such as Spark, Kafka, Airflow, or similar.

Responsibilities

• Design, build, and maintain scalable data pipelines.
• Develop and optimize data storage solutions including data lakes and warehouses.
• Implement and manage ETL/ELT workflows and orchestration tools.

Skills

Data engineering

Distributed systems

Cloud platforms (AWS, GCP, or Azure)

Python

Scala

Java

Data modeling

ETL/ELT workflows

Tools

Spark

Kafka

Airflow

dbt

Snowflake

BigQuery

Job description

Harrison Clarke is partnering with a high-growth, San Francisco–based technology startup that has recently secured $50M in Series A funding from leading venture capital firms. With a strong product-market fit and ambitious expansion plans, our client is now looking to hire a Senior Data Infrastructure Engineer to play a key role in scaling their data capabilities.

The Role

This is a unique opportunity to join at an early stage and take ownership of building and evolving the company’s data infrastructure. You will be instrumental in designing scalable systems that support analytics, product development, and business intelligence as the company continues its rapid growth.

Working closely with engineering, product, and data teams, you will help lay the foundation for a modern, robust, and efficient data platform.

Key Responsibilities

• Design, build, and maintain scalable data pipelines (batch and real-time)
• Develop and optimize data storage solutions, including data lakes and warehouses
• Implement and manage ETL/ELT workflows and orchestration tools
• Enhance data reliability, observability, and system performance
• Collaborate cross-functionally to enable data-driven product and business decisions
• Establish best practices around data governance, security, and quality

Requirements

• 5+ years of experience in data engineering or data infrastructure roles
• Strong background in distributed systems and cloud platforms (AWS, GCP, or Azure)
• Hands‑on experience with tools such as Spark, Kafka, Airflow, or similar
• Proficiency in Python, Scala, or Java
• Experience working with large-scale datasets and data modeling
• Strong problem‑solving skills and a pragmatic engineering mindset

Preferred Experience

• Background in high‑growth or venture‑backed startup environments
• Familiarity with modern data stack tools (e.g., dbt, Snowflake, BigQuery)
• Exposure to infrastructure‑as‑code and CI/CD pipelines

For more information or a confidential discussion, please reach out to Harrison Clarke directly.