Most small teams don't have a data problem, they have a plumbing problem. The same CSV and Excel exports get cleaned by hand every week, numbers from two systems never match, and reports break when a column changes.

I build Python and SQL pipelines that pull your data together, clean it, check it and load it into a database you can report from. Then it runs the same way every time.

Why work with me

In my current role I build and run batch and near real-time pipelines for banking data, ingesting 1TB+ from Oracle, IBM DB2 and MongoDB with Informatica, Spark and SQL, with daily data quality checks and reconciliation. Before that I built 8+ API integrations between business applications and automated workflows processing 20K+ records a day. I bring the same habit to smaller projects: every row is accounted for, nothing is silently dropped.

What I can build for you

• Python ETL pipelines from CSV, Excel, JSON, APIs or databases

• Data cleaning: duplicates, date and text formats, missing values, mismatched IDs

• Loading into SQL Server, PostgreSQL or MySQL with a simple, reporting-ready schema

• Data quality rules plus a reconciliation check (rows in = rows loaded + rows rejected)

• Faster SQL: query tuning, views and stored procedures

• PySpark jobs when the data is too large for a single script

What you receive

• Working, tested pipeline code that you own

• Clean tables in your database, or clean output files

• A rejects file listing every row that failed a rule, and why

• A short README on how to run and change the pipeline

• A handover walkthrough (call or written)

How it works

You share sample data and tell me where it needs to end up.

I send a short plan: sources, cleaning rules, target tables and timeline. Work starts once you approve it.

I build and test on your sample and keep you updated.

You review the output and I make the agreed changes.

What I need from you

• A sample of each data source, or read access

• Where the clean data should go

• Any business rules (for example, how to treat refunds or duplicate customers)

The starting price covers one pipeline with up to 3 sources and one destination. Larger or ongoing work is quoted after I've seen your data.