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Pipelines and Warehouses

Data Engineering ServicesThat Put Your Data to Work.

Most companies are sitting on goldmines of data with no pipeline to turn it into decisions. We build the infrastructure to collect, clean, transform, and serve your data where you need it.

10x
Faster Reporting
99.9%
Pipeline Reliability
60%
Reduction in Manual Reports
< 1 hr
Data Freshness
The Challenge

Sound Familiar?

Data problems are invisible until they're expensive. By the time the business notices, months of bad decisions have already been made.

Data Trapped in Silos

Sales in Salesforce, product data in Postgres, marketing in spreadsheets. No one can see the full picture.

No Single Source of Truth

Three teams pull the same metric and get three different numbers. Decisions stall while everyone argues about the data.

Manual Reporting

Someone spends 10 hours a week copying data into spreadsheets. That's not analysis - that's data entry with extra steps.

Inconsistent Data Quality

Nulls where there shouldn't be, duplicates in your customer table, timestamps in three different formats. The data can't be trusted.

Our Data Engineering Capabilities

From raw event data to boardroom dashboards. We handle the full data layer.

ETL and ELT Pipeline Design and Build

Reliable data pipelines that extract from any source, transform to your schema, and load where your team needs it.

Data Warehouse Setup

Snowflake, BigQuery, and Redshift setup with schema design, user management, cost controls, and query optimization.

Real-Time Streaming Pipelines

Kafka-based event streaming for use cases that can't wait for a nightly batch run - fraud detection, live dashboards, and triggers.

Data Quality and Monitoring

Automated checks on freshness, completeness, and consistency. Alerts before bad data reaches your dashboards or models.

Business Intelligence Dashboards

Looker and Metabase dashboards that give every team the metrics they own, without waiting for the data team.

Data Governance and Documentation

A data catalog, lineage tracking, and column-level documentation so anyone in the company can find and trust the data they need.

What We Build

Data infrastructure built around the decisions your business actually needs to make.

SaaS Product Analytics

  • User event tracking and funnels
  • Feature adoption and retention metrics
  • Cohort and LTV analysis
  • Real-time usage dashboards

Marketing Attribution Pipelines

  • Multi-touch attribution modeling
  • Ad spend consolidation across channels
  • Campaign ROI reporting
  • UTM tracking and hygiene

Financial Reporting Infrastructure

  • Revenue recognition pipelines
  • ARR and churn dashboards
  • Investor reporting automation
  • Audit-ready data lineage

Operational Dashboards

  • Support ticket volume and SLA tracking
  • Engineering incident metrics
  • Supply chain and fulfillment KPIs
  • Cross-functional OKR tracking

How We Build Your Data Stack

A methodical process that gets your team from "we can't trust this data" to "we run on this data."

01

Data Audit and Source Mapping

We inventory every data source, understand what questions the business needs to answer, and document what's missing or broken today.

02

Warehouse and Schema Design

We design the dimensional model or data vault schema that will support your reporting needs at scale without requiring constant rework.

03

Pipeline Build and Orchestration

ETL and ELT pipelines built in Airflow or native warehouse tooling, with dbt for transformation and full lineage tracking.

04

Data Quality Checks and Monitoring

Automated tests for freshness, completeness, and referential integrity. Slack alerts when something breaks before it becomes a crisis.

05

Dashboard Delivery and Handoff

Business-facing dashboards in Looker or Metabase, documentation of all models and metrics, and training so your team can self-serve.

Our Data Stack

Best-in-class tools that work together. We pick the right stack for your scale, not the most expensive one.

Python
Apache Airflow
dbt
Snowflake
BigQuery
Redshift
PostgreSQL
Kafka
Spark
Fivetran
Looker
Metabase
AWS S3
Terraform
Proof

Relevant case studies

Real outcomes from teams we shipped this exact work for.

Staff Augmentation for HeartFlow — HeartFlow
HeartFlow

Staff Augmentation for HeartFlow

  • 40% Faster Development
  • 99.99% Uptime
  • Zero Security Incidents
Read the story
Cloud Platform Frontend for ML/Kubernetes — ML Platform Provider
ML Platform Provider

Cloud Platform Frontend for ML/Kubernetes

  • 10x User Adoption
  • 3x Faster Workflows
  • 95% User Satisfaction
Read the story
Voice Analytics Platform Engineering — VoiceBase (acq. LivePerson)
VoiceBase (acq. LivePerson)

Voice Analytics Platform Engineering

  • 40% Faster Development
  • 2x Pipeline Throughput
  • Zero Incidents
Read the story

Ready to Turn Your Data Into Decisions?

Tell us about your data sources and what you're trying to measure. We'll scope a plan and get moving fast.