Fractional Data Engineer

Client Case Studies

Real projects. Real results. No full-time hire required.

Who We Work With

Most of our clients come to us at the same moment: the business is growing, the data questions are getting harder, and whoever's been holding things together is running out of runway. They need someone who's built this before - not a junior hire learning on the job, and not a $300K full-time engineer for a problem that doesn't need one yet.

We work with SaaS and tech-enabled companies between 10 and 200 people who are at exactly that moment.

Case Study 01

Building a dbt Data Foundation from Scratch: A Case Study for Startups Without a Data Team

Health tech · ~50 employees · No data person, just a CEO, AI, and a lot of manual checks. Now 12 people rely on the same infrastructure.

0 → 1

dbt data foundation built from scratch

10 hrs/week

given back to the CEO by eliminating manual data validation

Automated

data quality checks running continuously

Tech: dbt · dbt Cloud (free tier) · PostgreSQL · Data Modelling · dbt Tests · Calculated Columns · dbt Documentation

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Case Study 02

Building a Self-Serve Analytics Culture with Metabase: A Case Study for Startups Without a Data Team

Health tech · ~50 employees · 11 non-technical users now making decisions from data, without asking anyone for help

0 → 1

Metabase built and adopted from scratch

11

non-technical users actively using self-serve analytics

4 departments

onboarded: marketing, sales, operations, C-level

Tech: Metabase · Metabase (basic plan) · dbt · PostgreSQL · Workshop Design · Notion · Data Governance · Self-Serve Analytics

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Case Study 03

Building an AWS Event Tracking Pipeline from Scratch: A SaaS Case Study

Flexible office marketplace SaaS · ~150 employees · Fast-growing, investment-backed · Full Pentaho to AWS migration

2 weeks

to get the pipeline live

5,000+ events/day

processed through the pipeline

Pentaho to AWS

legacy infrastructure modernised

Tech: AWS Lambda · AWS S3 · AWS Glue · PostgreSQL · Segment.io · Data Modelling · Data Partitioning · Cloud Infrastructure

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Case Study 04

Replacing a Legacy ETL Tool with AWS: A SaaS Migration Case Study

Flexible office marketplace SaaS · ~150 employees · Fast-growing, investment-backed · Full Pentaho to AWS migration

6 months

to fully replace Pentaho with a modern AWS stack

4 sources integrated

PostgreSQL, Pipefy, HubSpot, Segment.io

30+ pipelines

running in Airflow

Tech: Apache Airflow · AWS Lambda · AWS S3 · PostgreSQL · Pipefy · HubSpot · Segment.io · Python · SQL · Parquet · Data Modelling

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Case Study 05

Building a Data Lakehouse from Scratch on AWS: A Case Study for Complex Organizations

Multinational organization · ~500 employees · $32M revenue · No prior data infrastructure

40% under budget

data platform delivered

130+ pipelines

running in Airflow across all sources

72 hours

from development to production for new pipelines

Tech: Apache Spark · Apache Airflow · Apache Iceberg · AWS · Terraform · Docker · PostgreSQL · Salesforce · Freshdesk · Google Analytics · Metabase · Python · SQL

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