Member of Technical Staff, Data Engineering

Build data infrastructure from the ground up

Own the architecture and implementation of a data warehouse, ingestion pipelines, transformations, and product analytics foundations. This full-time remote role is for a staff-level engineer who has built data infrastructure from scratch and operated it in production.

The goal is to turn fragmented operational and product information into reliable data that people and autonomous agents can discover, query, and use. The systems support independent analytics, automated decisions, and more capable internal workflows.

Responsibilities

• Design and implement the warehouse, ingestion infrastructure, ETL and ELT pipelines, and core data models.
• Create reliable, documented datasets and interfaces that agents can safely discover and query.
• Transform inconsistent operational and product data into trusted information sources.
• Build analytics infrastructure that lets engineering, product, and business teams answer questions without manual data requests.
• Establish event tracking, instrumentation, reporting, and data models for product usage and performance analysis.
• Apply AI coding agents and automation to pipeline development, validation, documentation, monitoring, and troubleshooting.
• Establish data quality, observability, governance, and scalable architectural practices from the outset.
• Mentor engineers and lead technical standards and architectural decisions through practical implementation.

Required background

• Staff-level expertise building and operating production data systems, including direct ownership of a new system from initial design through implementation.
• Deep understanding of warehouses, ETL and ELT architecture, data modeling, orchestration, and distributed processing.
• Strong SQL, Python, and software engineering fundamentals.
• Experience with tools such as Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Dagster, or equivalent technologies.
• Knowledge of data quality, lineage, observability, access controls, and production reliability.
• Experience designing analytics infrastructure for product insight and operational decisions.
• Daily use of AI coding agents and active automation of repetitive development and data tasks.
• Sound architectural judgment across scalability, simplicity, performance, and development speed, with demonstrated mentoring and technical leadership.

Helpful experience

Experience as an early or founding data engineer responsible for an initial data system is useful. Other valuable experience includes supporting both traditional analytics and AI applications, building semantic layers or data discovery tools, and providing structured data interfaces for autonomous agents.

Substantial automation of pipeline development, validation, or maintenance with AI agents is helpful. The role also values practical design judgment and comfort moving between architecture, production pipelines, analytical modeling, and debugging.

Compensation and benefits

The national base salary range is $200,000 to $260,000. Employees are eligible for equity and may receive performance bonuses depending on the role and applicable policies.

Benefits include up to 100% reimbursement of health insurance premiums, paid time off, and a 401(k) plan with an employer match.