Data Engineering built for Manufacturing companies
What is Data Engineering?
We turn scattered data into pipelines your business can actually trust and query. For Manufacturing companies, this means navigating ISO 9001, OSHA (US) while shipping fast.
Who needs Data Engineering for Manufacturing?
- Legacy equipment lacking modern connectivity
- Predictive maintenance data scattered across systems
- Supply chain visibility gaps
- Data scattered across disconnected systems
- Reports that disagree depending on who pulls them
Best Data Engineering company
Factory-floor software has to survive unreliable connectivity and decades-old equipment, not just modern offices.
Every Manufacturing company eventually needs reliable Data Engineering — we make that step less risky.
Talk to our Manufacturing Data Engineering specialists this week
Book a free 30-minute discovery callWhat's actually blocking Manufacturing businesses from shipping Data Engineering
- Legacy equipment lacking modern connectivity
- Predictive maintenance data scattered across systems
- Supply chain visibility gaps
- Quality control processes still largely manual
- ERP systems too rigid for plant-floor realities
Our process for delivering Data Engineering to Manufacturing clients
Data warehouse architecture (Snowflake, BigQuery)
ETL/ELT pipeline development
Data quality monitoring and alerting
BI dashboard integration
Data governance and access controls
Core Technology Stack
SnowflakeBigQueryAirflowdbtPythonKafkaAWS Glue
Timeline, investment & compliance
Typical timeline
8-16 weeks
Typical investment
$25,000 - $140,000
Data Engineering engagements in this combination typically need to account for:
- ISO 9001
- OSHA (US)
- CE marking (EU)
- Industry 4.0 standards
Our Approach
The hardest part of Manufacturing work is rarely the feature list — it's legacy equipment lacking modern connectivity while staying inside ISO 9001. We structure sprints and code review around that constraint rather than treating compliance as a final pass.
See our case studiesTalk to our Manufacturing Data Engineering specialists this week
Get a free project cost estimateFrequently Asked Questions
Most Data Engineering engagements take 8-16 weeks, depending on scope and how clear the requirements are upfront. We'll give you a firm timeline estimate after a short discovery call, not a generic range.
Data Engineering projects with us typically range from $25,000 - $140,000, scaled to the complexity of your requirements. We provide a detailed, itemized estimate before any work begins so there are no surprises mid-project.
For data engineering, we typically work with Snowflake, BigQuery, Airflow, dbt, chosen based on your specific scalability and integration requirements. We're not tied to a single stack and will recommend the right tools for your situation rather than our default.
A typical data engineering engagement includes data warehouse architecture (snowflake, bigquery), along with the other deliverables outlined in our proposal, such as documentation and a post-launch support window. The exact scope is tailored to your project during discovery.
Most clients come to us for data engineering because of data scattered across disconnected systems, among other related challenges. We start every engagement by mapping your specific pain points before writing a single line of code.
We've delivered multiple manufacturing projects addressing challenges like legacy equipment lacking modern connectivity. We helped a manufacturer cut unplanned downtime by 28% with a predictive maintenance dashboard.
For manufacturing clients, we pay close attention to ISO 9001, OSHA (US), building these requirements into the architecture from day one rather than retrofitting them later. We'll confirm which specific regulations apply to your business during discovery.
The most common challenges we solve for manufacturing clients include legacy equipment lacking modern connectivity and predictive maintenance data scattered across systems. We tailor our discovery process to surface the specific version of these problems your business faces.