Data Engineering, BI and Analytics
Your company's data already exists — in the ERP, the CRM, spreadsheets and APIs. We bring it together in one reliable, automatically updated source, so decisions come from numbers instead of guesses.
Data engineering is JJ Software's deepest expertise: our founder has worked as a data engineer since 2021, building pipelines and data architectures with Databricks, Python and Azure on projects for large companies, and holds the Microsoft Certified: Azure Data Engineer Associate certification. We bring the same practice to companies of any size.
The work starts with the questions the business needs answered — revenue by channel, margin by product, overdue payments, idle stock — and only then gets to tools. We map where each piece of data comes from, build the pipelines that extract, clean and join those sources, and organize the result in layers (raw, cleaned and analysis-ready), following the lakehouse pattern.
In the end, every number has a known source, a documented rule and tests that flag when something looks off. Dashboards and reports refresh on their own, and your team stops copying and pasting spreadsheets every week. When volumes are small, a lean setup does the job; when they grow, the architecture is ready to scale.
What's included
- Assessment of your data sources and the metrics that matter to the business
- ETL/ELT pipelines in Python, SQL and Spark, scheduled and monitored
- Data lakehouse on Databricks and Azure, or lower-cost alternatives
- Integration with ERPs, CRMs, spreadsheets, databases and APIs
- BI dashboards and reports that update automatically
- Data quality tests, failure alerts and documentation
Benefits
- Data engineering experience from large companies, working directly with the person doing the work
- A single source of truth instead of spreadsheets that disagree
- Reports that refresh themselves, with no recurring manual work
- Architecture sized to your volume and budget, without over-engineering
- Data and infrastructure in your company's own accounts, so you're never locked in
Questions about this service
We're a small company. Does data engineering make sense for us?
Yes, as long as there's a business question to answer. For small volumes, a lean setup — a managed database, a few scheduled pipelines and a BI dashboard — is cheap to run and already saves hours of spreadsheet work every week. Databricks and a lakehouse come in when volume and complexity call for them.
Which tools do you work with?
Our core is Python, SQL and Spark, with Databricks and Microsoft Azure, where we hold a data engineering certification. We also integrate databases such as PostgreSQL and SQL Server, public and private APIs, and the BI tools your team already uses.
Can you improve a data setup we already have?
Yes. Often the best start is reviewing pipelines that break, slow queries or high cloud bills, and fixing what pays off most before building anything new.
Got a project in mind?
Tell us what you need to build and we'll get back to you with a straightforward proposal.