At Lahzo, we’re on a mission to help companies with complex sales cycles and high customer acquisition costs unlock meaningful revenue growth through a combination of precision-targeted demand generation and autonomous AI agents. In short? We’re conversion-obsessed, bringing together cutting-edge technology, deep go-to-market expertise, and a relentless focus on revenue outcomes.
Backed by a team of experienced founders and technologists, we're building a platform that doesn't just generate leads—it intelligently orchestrates the end-to-end buyer journey, reducing friction, increasing velocity, and turning intent into revenue.
We're seeking a seasoned Data Engineer I/II to join our rapidly growing tech startup. Every client report, experiment, and business decision runs on our data. This role exists to own that foundation. Your job is to make data available and trustworthy. That means building and maintaining ETL pipelines, writing data transformations and table logic, running data quality monitoring and anomaly detection, and onboarding new clients onto the full data infrastructure from day one.
We are looking for someone who finds deep satisfaction in infrastructure that just works — who thinks seriously about monitor coverage, catches problems before clients do, and takes pride in building systems that are reliable and built to last. In the first 90 days you will be executing known tasks and getting deep context on our stack and clients. Beyond that, we expect you to diagnose data problems, identify the right levers, and drive improvements to the systems and processes that keep data quality high as we scale.
We are looking for someone who wants to build a career around deep technical execution — someone who finds real satisfaction in owning complex infrastructure end-to-end and growing into the go-to expert on data systems as the company scales.
What You’ll Do
- 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.
What We’re Looking For
- 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
Nice to Have
- Dataform or dbt
- Terraform on GCP
- BigQuery — partitioning, clustering, cost optimization
- Data quality monitoring tools — Monte Carlo, Great Expectations, or similar
- Multi-tenant or per-client data isolation patterns
- Cloud Functions or Cloud Run for ETL pipelines
- A/B experiment pipelines or marketing attribution models
- Hex or similar self-serve analytics tooling — building data products that non-technical teams can use independently
Why Join Us
- Real ownership, real scale - You will own the data infrastructure that powers hundreds of millions of ad impressions and thousands of AI agent conversations every month — across 10+ live client environments.
- An interesting problem space - We sit at the intersection of AI agents, programmatic advertising, and multi-channel attribution. The data problems are genuinely hard and the stakes are real — every pipeline you own is tied directly to client revenue.
- A stack worth mastering - BigQuery, Dataform, Terraform, Monte Carlo, Hex, Cloud Functions. Production workloads, real clients, no toy data. And we are actively building toward self-hosted AI infrastructure.
- Small team, high context, fast growth - You will know every pipeline and why it exists. No mystery tables, no hand-offs to teams you have never met. And you will grow with the company as we scale into new verticals and client markets.
Compensation
- Base: $100k - $130k
- Equity: Participation in our equity award program.
Benefits
Benefits include medical, vision, dental, unlimited PTO, remote-first environment, a 401k and most of all, a collaborative, growth-focused, high-trust, high-performance environment where your ideas matter.
Timing
We are looking to fill this position as soon as we find the right candidate.
Equal Opportunity Employer
Lahzo appreciates your interest in our company as a place of employment. It is Lahzo’s policy to provide equal opportunity for employment to all qualified employees and applicants, regardless of race, religion, religious affiliation, ancestry, citizenship status, marital status, familial status, sexual orientation, gender identity, color, creed, national origin, sex, age, disability, or veteran status or any other characteristic protected by local, state or federal law. This policy applies to all areas of employment including recruitment, placement, training, transfer, promotion, termination, pay, and other forms of compensation and benefits. Lahzo will provide reasonable accommodations to qualified individuals.
Skills Required
- Hands-on data engineering experience building and maintaining production pipelines end-to-end
- Strong SQL including complex aggregations, window functions, and multi-step transformations
- Data transformation experience across multiple environments (dev/staging/prod)
- Infrastructure as code experience to provision and manage cloud data infrastructure and permissions
- Python for data engineering (ETL scripts, pipeline tooling, automation)
- Data quality mindset: setup monitoring, tune alerts, and resolve data issues
- Systematic debugging: trace issues end-to-end across the data stack
- AI-fluent but grounded: use AI tools productively while understanding underlying systems
- Motivated by technical impact and ownership of complex infrastructure
- Dataform or dbt
- Terraform on GCP
- BigQuery knowledge (partitioning, clustering, cost optimization)
- Data quality monitoring tools (Monte Carlo, Great Expectations, or similar)
- Multi-tenant or per-client data isolation patterns
- Cloud Functions or Cloud Run for ETL pipelines
- A/B experiment pipelines or marketing attribution models
- Hex or similar self-serve analytics tooling
What We Do
Building industry-specific AI growth solutions to complete a perfect revenue circle: data-driven marketing driving customers to an AI sales agent. Consistent delivery, immediate access, and infinitely scalable.
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