Data Engineering
Your data pipeline, actually working for you.
We build automated data pipelines that collect, clean, transform, and route your data — so your systems stay in sync, your decisions stay accurate, and your team stops doing manually what should be automatic. Serving businesses across the United States.
3+ hrs
Saved weekly on reporting
6
Avg. sources unified
< 4h
Data freshness
what it is
What is data pipeline development and ETL?
A data pipeline is the automated process that moves data from where it's generated — your CRM, e-commerce platform, ad accounts — to where it's useful, cleaned, transformed, and ready to query. Without one, that work happens manually in spreadsheets.
Data pipelines are the foundation for custom analytics dashboards — get the infrastructure right and everything downstream becomes faster, more reliable, and more accurate.
the problem
Does this sound familiar?
Data scattered across 5+ tools. Shopify, Meta Ads, your CRM, your inventory system — none of them talk to each other and none of them agree on the numbers.
Hours lost to manual reporting. Someone on your team is pulling exports, pasting into sheets, and reconciling data every week. That's expensive and error-prone.
Decisions made on stale data. By the time you see what happened, it's too late to act. You need data that's hours old, not weeks old.
No single source of truth. Different people in your business are looking at different numbers and drawing different conclusions. That's a pipeline problem.
what we build
What we deliver
Multi-source ETL pipelines
Extract from APIs, CSVs, databases, and webhooks — clean, normalize, and load into your warehouse on a schedule.
dbt transformation models
Business logic defined as SQL models — CAC, LTV, margin, cohorts — version-controlled and testable.
Scheduled automation with Airflow
Pipelines that run on a schedule, retry on failure, and alert you when something goes wrong.
Real-time sync pipelines
Event-driven pipelines that update your warehouse minutes after something changes in a source system.
Data quality monitoring
Automated checks that flag anomalies — missing data, unexpected nulls, values out of range — before they reach your dashboard.
how it works
How we build your data pipeline
Audit your data landscape
We map every data source, understand the shape of each, and identify the joins and transformations needed.
Design the pipeline architecture
Extraction strategy, transformation logic, load targets, scheduling, and failure handling — all defined before we build.
Build incrementally
We ship one source at a time, validating each before adding the next — so you see value early and problems surface quickly.
Deploy & document
Running on your infrastructure with full documentation of every model, schedule, and data contract.
tech stack
Technology we use
Extraction
Python + APIs
Transformation
dbt
Scheduling
Apache Airflow
Warehouse
Supabase / PostgreSQL
Monitoring
Alerting + logs
Hosting
Vercel / AWS
Common questions about data pipelines & ETL.
A data pipeline is the automated process that moves data from where it's generated — your CRM, e-commerce platform, ad accounts — to where it's useful, cleaned, transformed, and ready to query. Without one, that work happens manually in spreadsheets.
ETL stands for Extract, Transform, Load. It's the process of pulling data from multiple source systems, cleaning and transforming it into a consistent format, and loading it into a data warehouse — creating a single source of truth across tools like Shopify, Meta Ads, CRMs, and inventory systems.
Most projects are completed in 2–6 weeks depending on the number of sources, complexity of transformations, and infrastructure requirements. We build incrementally — shipping one source at a time so you see value early.
We build with Python for extraction, dbt for transformations, Apache Airflow for scheduling, and Supabase or PostgreSQL as the data warehouse. Monitoring is handled through alerting and logs deployed on Vercel or AWS.
Scheduled pipelines typically keep data under 4 hours fresh. For event-driven use cases, we can build real-time sync pipelines that update your warehouse within minutes of a change in a source system.
related work