Data Engineer I/II

LAHZO

Data Engineer owning data infrastructure for Lahzo's data operations. Focused on building reliable pipelines and ensuring data quality in a startup environment.

Posted 6/18/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $100,000 - $130,000 per yearWebsite

Tech Stack

Tools & technologies

CloudETLPythonSQL

About the role

Key responsibilities & impact

ETL pipeline development — Build and maintain data ingestion pipelines that move data reliably from source into the warehouse. Own the infrastructure end-to-end.
Data transformation and table logic — Build and maintain transformation models — client-specific and shared. Handle schema changes, new table configurations, and the ongoing queue of transformation requests.
Data quality and anomaly detection — Own data quality monitoring end-to-end: setup, threshold tuning, alert triage, and fixes. Extend coverage through assertions and automated alerting. Turn reactive monitoring into proactive coverage.
Client onboarding infrastructure — Every new Lahzo client gets a dedicated cloud project, service accounts, permissions, and registered data pipelines. You own this process from infrastructure provisioning to first clean pipeline run.
Pipeline reliability and debugging — Understand the full data flow from raw event ingestion through final reporting tables. Debug issues across the stack end-to-end.
Ad hoc data requests — First responder for data requests from internal teams — confirming requirements, making schema or pipeline changes, and keeping the queue clear so the team stays focused on higher-leverage work.

Requirements

What you’ll need

Hands-on data engineering experience — you have built and maintained production pipelines end-to-end, not just written queries
Strong SQL — production-quality, comfortable with complex aggregations, window functions, and multi-step transformations
Data transformation experience — you have built and maintained SQL-based transformation pipelines across multiple environments (dev / staging / prod)
Infrastructure as code — you can provision and manage cloud data infrastructure, set up permissions, and debug access issues without hand-holding
Python for data engineering — ETL scripts, pipeline tooling, and automation
Data quality mindset — you understand what good pipeline health looks like, know how to set up monitoring, tune alerting thresholds, and drive issues to resolution
Systematic debugger — when something breaks, you trace it end-to-end across the stack rather than stopping at the first symptom
AI-fluent but grounded — you use AI tools to move faster and validate more thoroughly, and you still understand what is happening underneath. You are not chasing the next shiny tool instead of shipping.
Motivated by technical impact — you want to be the person who truly understands the systems, and you see growing expertise as the path to more interesting and higher-impact work

Benefits

Comp & perks

medical
vision
dental
unlimited PTO
remote-first environment
a 401k
collaborative, growth-focused, high-trust, high-performance environment where your ideas matter

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

ETL pipeline developmentdata transformationSQLinfrastructure as codePythondata quality monitoringdebuggingdata ingestionschema managementautomated alerting

Soft Skills

problem-solvingattention to detailcommunicationproactive mindsetcollaborationtechnical impact motivationsystematic debuggingclient onboardingadaptabilitytime management