Member of Technical Staff, Data Engineering

micro1; United States; Remote; USD 180,000 - 240,000; Full time

Job summary

micro1 is seeking a Staff Data Platform Engineer to own and build the data warehouse, ingestion pipelines, ETL/ELT, and product analytics foundations from zero to production. You will shape reliable, AI-ready data systems and enable self-service analytics across engineering, product, and business teams.

You will mentor engineers, drive architectural decisions, ensure data quality, observability, and scale, and partner with product and AI teams to unlock trusted insights for automated

Qualifications

• Experience designing and implementing data warehouses from scratch.
• Strong background in data ingestion, orchestration, and pipeline reliability.
• Ability to design AI-ready data foundations for self-serve analytics.
• Proven track record leading data engineering teams and architectural decisions.

Responsibilities

• Own the architecture and implementation of the data warehouse and ingestion pipelines.
• Define and enforce data quality, observability, and governance standards.
• Build scalable, well-documented data models and interfaces for AI agents.
• Mentor engineers and lead architectural decisions through hands-on execution.
• Collaborate with product and analytics teams to enable self-serve analytics.

Skills

Data Platform Architecture

ETL/ELT Pipelines

AI Agents & Agent-Ready Data

Technical Leadership

Job description

The Role

This is a Staff-level, hands-on engineering role for someone who has built data infrastructure from zero to production and knows how to turn fragmented operational data into reliable, accessible, and actionable systems. You'll own the architecture and implementation of our data warehouse, ingestion pipelines, transformations, and product analytics foundations. We're building an AI-native organization where both humans and autonomous agents need access to trustworthy, well-structured data. You'll design the systems that make this possible, enabling self-service analytics, automated decision-making, and increasingly intelligent workflows across the company. 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.

Required skills

Data Platform Architecture & Engineering, ETL/ELT Pipelines & Data Orchestration, AI Agents & Agent-Ready Data Systems, Technical Leadership & Systems Architecture