Data Engineer I/II

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LAHZO

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2023

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

Artificial Intelligence • SaaS • B2B

LAHZO is an AI-driven growth partner that provides modular AI Sales Agents and integrated digital marketing solutions to help dealers and enterprises attract, engage, and convert customers 24/7. The platform combines proprietary data sets, geospatial analytics, CRM and inventory integrations, and hyper-targeted advertising to deliver personalized ad-to-agent experiences, smart retargeting, and full-funnel marketing. Lahzo focuses on industry-specific deployments (e. g. , RV, marine, powersports, heavy agriculture, industrial) and positions its solution as a scalable, brand-tailored SaaS offering that boosts lead conversion and funnels qualified leads to sales teams.

📋 Description

• 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

• 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

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