Technology & Tools
Data tools we work with.
We're tool-agnostic. We pick platforms based on your existing infrastructure, your team's skill level, and what your data actually requires — not vendor partnerships.
The stack matters less than how it's built.
Every client's data infrastructure is different. Some have years of investment in Azure. Others are starting from scratch. We've deployed these tools across 600+ projects and know where each one fits — and where it doesn't.
Below is what we work with most. If your stack isn't listed, that's fine — we've likely seen it.
Data Warehouses
Where your data lives after we consolidate it. We size the warehouse to your workload — not the vendor's pricing page.
Snowflake↗
Our most common recommendation for clients who need scalable cloud storage and compute with usage-based pricing.
Google BigQuery↗
Strong fit for organizations already on Google Cloud. Serverless, so there's nothing to tune or manage.
Amazon Redshift↗
Fully managed cloud data warehouse from AWS, optimized for large-scale analytics and complex queries.
Databricks↗
Unified analytics platform combining data engineering, data science, and business analytics on a lakehouse architecture.
PostgreSQL↗
Open-source relational database used as an analytical data store, operational database, and foundation for many cloud data platforms.
Microsoft SQL Server↗
Enterprise relational database platform with integrated analytics, reporting, and machine learning services.
Data Integration & ETL
Getting data from source systems into the warehouse. We automate this so your team stops copying and pasting between systems.
Fivetran↗
Pre-built connectors to 300+ sources. We use this when clients need fast, reliable replication without custom code.
Stitch↗
Lightweight, open-source-friendly ETL. Good option for smaller data volumes or tighter budgets.
Azure Data Factory↗
The right choice when the client's infrastructure is already on Azure and they need orchestration across Microsoft services.
AWS Glue↗
Serverless ETL on AWS. We use it for clients with existing AWS investments who need discovery and transformation at scale.
Airbyte↗
Open-source data integration platform with 300+ connectors for extracting and loading data from any source.
Transformation & Orchestration
Cleaning, modeling, and scheduling the data after it lands. This is where raw data becomes something your team can actually query.
dbt↗
Version-controlled SQL transformations with testing built in. We use dbt on nearly every data engineering engagement.
Apache Airflow↗
Workflow orchestration for complex pipelines — scheduling, dependencies, retries, and monitoring in one place.
n8n↗
Open-source workflow automation platform for connecting APIs, transforming data, and building automated pipelines with a visual editor.
Related Services
Not sure which tools are right for your data?
We'll assess your current stack and recommend what fits — no vendor bias.