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Member of Technical Staff, Data Engineering

micro1· Core team
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Remote$200k - $260kFull-timePosted yesterday

About the role

Staff-level data engineering role focused on building and operating a production-grade data platform, including data warehouse, ingestion, transformations, and product analytics foundations for an AI-native organization.

Responsibilities

  • Build our data platform from zero: Architect and implement our internal data warehouse, ingestion infrastructure, ETL/ELT pipelines, and core data models.
  • Create agent-ready data foundations: Design reliable, well-documented datasets and interfaces that AI agents can safely discover, query, and use.
  • Turn messy data into trusted systems: Transform fragmented operational and product data into consistent, high-quality sources of truth.
  • Enable self-service analytics: Build the infrastructure that allows engineering, product, and business teams to answer questions independently without relying on manual data requests.
  • Own product analytics infrastructure: Establish the event tracking, instrumentation, data models, and reporting foundations needed to understand product usage and performance.
  • Automate data operations: Leverage AI coding agents and intelligent automation to accelerate pipeline development, data validation, documentation, monitoring, and troubleshooting.
  • Build for reliability and scale: Establish data quality standards, observability, governance, and scalable architectural patterns from the beginning.
  • Raise the engineering bar: Mentor engineers, establish strong data engineering practices, and lead architectural decisions through hands-on execution.

Qualifications

  • Staff-level engineering expertise with extensive hands-on experience building and operating production data platforms.
  • Proven greenfield experience: design and implementation of a data platform from scratch.
  • Deep understanding of data warehouses, ETL/ELT architectures, data modeling, orchestration, and distributed data processing.
  • Strong proficiency in SQL and Python, with software engineering fundamentals for reliable data infrastructure.
  • Experience with Snowflake, BigQuery, Redshift, Databricks, dbt, Airflow, Dagster, or equivalent tools.
  • Strong understanding of data quality, lineage, observability, access controls, and production data reliability.
  • Experience designing analytics infrastructure to support product insights and operational decision-making.
  • AI-native engineering habits: using AI coding agents and automating repetitive tasks.
  • Ability to make pragmatic architectural decisions balancing scalability, simplicity, performance, and engineering velocity.
  • Demonstrated technical leadership including mentoring engineers and establishing engineering standards.

Skills

Required:Staff-level engineeringGreenfield data platform designSQLPythonData warehouses & ETL/ELTTech stack familiarityData quality & observabilityAI-native engineeringTechnical leadership

Benefits

  • equity compensation
  • performance-based bonuses (subject to role and company policies)
  • up to 100% health-insurance premiums reimbursement
  • paid time off
  • 401(K) plan with company match
  • remote-first workforce support
Last updated Oct 25, 2026. Interested? Apply on the company site.

About micro1

Data lab to train frontier models & evaluate agents

We’re building the infrastructure for advancing intelligence through expert human data, real-world training environments, and contextual evaluations.

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