Founding Data Engineer (Pipelines)

Greylock Partners; San Jose (CA); On-site; USD 120,000 - 160,000; Full time

Job summary

A leading investment firm is seeking a Founding Data Engineer to design and operate a modern, open-source data lakehouse for handling large datasets. The candidate should have 5+ years of experience, be proficient in Python, and skilled in building data architectures. This role offers substantial growth opportunities while shaping the company's analytics infrastructure. Bonus points for cybersecurity experience and familiarity with relevant tools like Kafka, Spark, and PostgreSQL.

Qualifications

• 5+ years of relevant industry experience.
• Ability to design and operate modern data architectures.
• Experience in constructing robust, end-to-end data pipelines.

Responsibilities

• Design and operate a data lakehouse environment for large datasets.
• Construct robust, end-to-end pipelines from data intake to user access.
• Ensure platform performance, dependability, and accuracy at scale.

Skills

Building and managing very large data platforms

Streaming and batch data processing

Open-source technologies (Iceberg, PostgreSQL, Parquet)

Apache Kafka

Apache Spark

Apache Flink

Data transformation practices

Python proficiency

Technical documentation

Tools

Iceberg

PostgreSQL

Parquet

Neo4j

Job description

Early‑stage, cybersecurity investment (valued over $100M at Seed), founded by a successful serial entrepreneur, is looking to hire a Founding Data Engineer. Bonus points for prior industry experience in cybersecurity.

Our ideal candidate will be a seasoned data engineering specialist (with 5+ years relevant industry experience) who can help this company create its next generation of analytics infrastructure. Working closely with a highly‑experienced founding team, you will play a central role in shaping data architecture from the ground up and will have significant room for professional growth as the organization scales.

What the Role Involves

The position centers on designing and operating a modern, open‑source data lakehouse environment built to handle extremely large datasets. The engineer will be responsible for constructing robust, end‑to‑end pipelines—from data intake to processing to end‑user access—while ensuring the platform is performant, dependable, and accurate at massive scale.

Qualifications

• Demonstrated expertise in building and managing very large data platforms (multi‑petabyte range)
• Background in both streaming and batch data processing
• Hands‑on familiarity with open‑source technologies commonly used in lakehouse setups (e.g., Iceberg, PostgreSQL, Parquet, graph databases such as Neo4j)
• Strong experience with streaming and analytics frameworks like Kafka, Spark, or Flink
• Solid understanding of data transformation practices
• Advanced proficiency in Python
• Clear communication skills and the ability to produce strong technical documentation
• Bonus: experience with cloud service provider data ecosystems
• Bonus: knowledge of tools related to governance, data quality, and lineage