Data platforms that stay reliable at billions of events a day.
We design and build data platforms that handle real-world scale — from raw ingestion to live dashboards — so your teams always have the data they need to decide.
What We Build
Three practice areas
End-to-end data stack coverage — from raw pipeline to the dashboard your CEO uses every morning.
Data Engineering
We build the pipelines that move, transform, and deliver your data — batch at scale and in real time. ETL/ELT from any source, streaming with Kafka and Spark, and integration with Snowflake, BigQuery, and Databricks. Data quality and lineage included.
Data Warehouse & Modeling
A well-designed warehouse is the foundation of every data-driven organization. We design dimensional models, integrate data from operational systems and third-party APIs, optimize query performance, and implement governance policies that scale.
BI & Analytics
We turn raw data into dashboards and reports that decision-makers actually use. Interactive, always connected to live data, and designed for self-service — so teams stop waiting on data requests.
Case Studies
Work that shipped
Selected data platform projects from our portfolio — real results, anonymized where requested.
Client
Structural monitoring & IoT company
Scope
Real-time IoT sensor data platform on AWS
Built an end-to-end platform ingesting billions of sensor events per day using Apache Spark and InfluxDB. Query time reduced by 40% through time-series optimization. 99.9% uptime with Terraform-automated infrastructure and Grafana dashboards providing real-time operational visibility.
Client
Enterprise navigation software company
Scope
Petabyte-scale Cloudera/Spark stabilization
Identified and fixed root causes of corruption in a petabyte-scale Cloudera distribution. Optimized Spark job algorithms, enabling daily job runs that were previously too slow. Migrated from Cloudera to vanilla Hadoop with HA master, eliminating vendor lock-in entirely.
Client
Software design & consulting company
Scope
End-to-end AWS data platform: ETL, ML, and BI
Delivered a unified data platform covering the full lifecycle — raw ingestion through ETL to ML models and executive BI dashboards. Built on AWS with SageMaker for real-time predictions and QuickSight for cross-departmental reporting.
How We Engage
Four ways to work with us
Start with a fixed-scope audit, scale into a project, keep us on to run it. Engineers on every call — there is no sales team.
2 weeks · Fixed price
Data Platform Audit
A structured review of your current data architecture: pipeline reliability, warehouse design, cost efficiency, and analytics gaps. Delivered as a prioritized roadmap with effort estimates.
6–16 weeks
Pipeline & Warehouse Build
Fixed-scope delivery of a data pipeline, warehouse layer, or BI system. Clear milestones, weekly check-ins, handover with full documentation and runbooks.
Monthly · inside your team
Embedded Platform Engineers
One engineer or a full squad — sized to the roadmap, month by month. Senior engineers join your team, your tools, and your rituals, led by the same architect from day one.
Monthly · we run it
Managed Platform Operations
Senior engineers own your platform in production: on-call with a 30-minute response for incidents, upgrades, security patching, capacity and cost reviews, and a monthly written report. Your team keeps shipping features.
Our Standards
What we don't do
We work with companies that are serious about their data. That means being direct about the shortcuts we won't take.
Build warehouses without data quality checks — garbage in, garbage out
Dashboard sprawl disconnected from a reliable source of truth
Pipelines that work in dev but fail silently in production
Lock you into proprietary tools when open standards serve you better