07 / Platform & data
Data you can trust, in databases built to grow
I design, optimize and clean up databases: PostgreSQL schemas, migrations, reporting and automated data-quality checks.
The database is the foundation most companies think about only once it starts to crack: reports from two systems show different numbers, the application slows down as records pile up, and decisions rest on data nobody fully trusts. I fix these problems at the source, in the data model, the queries and the processes that feed them.
Data quality is where my experience runs unusually deep: in projects delivered in enterprise environments, including work connected with organizations such as PwC, Roche and E.ON, I built automated data validation, the machinery that checks day after day whether data is complete, consistent and in agreement across systems. I bring the same techniques to companies of every size.
You work directly with the person who designs the schema, writes the SQL and answers for the result, with no intermediaries relaying the problem. The scope varies: designing a database for a new product, rescuing a system that has slowed to a crawl, or untangling reporting in a company that has outgrown Excel.
What the service covers
Database design and data modelling
I design PostgreSQL schemas around real queries and future growth, not textbook theory. The data model comes documented, and schema changes go through versioned migrations rather than manual fixes on production.
- Schema and data-model design for your actual processes
- Schema migrations without downtime or data loss
- Supabase and cloud database implementations
- Data-model documentation for the team
Performance optimization and SQL development
I diagnose slow queries from measurements, not guesswork: execution-plan analysis, indexing, query rewrites and schema adjustments. I also write the complex reporting and analytics SQL your team is missing.
Reporting and data pipelines
I build reporting systems and ETL processes that combine data from multiple sources into one reliable place, replacing the monthly ritual of stitching numbers together from several systems and Excel.
- Data integrations between company systems
- ETL processes and data pipelines
- Reports and views prepared for BI tools
- Data synchronization between applications
Data quality and automated validation
I implement automated data-quality checks: consistency rules, reconciliation between systems and alerts when something drifts apart. Errors surface within hours, not at a board meeting where two reports disagree.
Security, backups and recovery
I tighten database access on a least-privilege basis and design a backup strategy with a tested restore procedure. We state plainly how much data and downtime the business can afford in the worst case, then build a plan that fits inside it.
Typical situations
- 01
Two reports from two systems show different numbers and nobody can say which one is right.
- 02
The application was fast with thousands of records, but today every data-heavy page takes seconds to load.
- 03
Backups supposedly “just run”, but nobody has ever checked whether anything can be restored from them.
- 04
Customer data lives in three systems plus Excel, and building a combined report costs someone several days every month.
What you can count on
A schema designed for real queries and data growth, with changes managed through versioned migrations.
Visibly faster queries and reports, with a clear explanation of what I changed and why.
Automated data-quality checks that catch discrepancies before they reach a management report.
A backup plan with restores that have actually been tested, not just backups that exist.
Technologies
- PostgreSQL
- SQL
- Supabase
- Python
- Amazon Redshift
- AWS Glue
- Amazon S3
Questions about this service
Usually not. Most performance problems are solved on the database side: indexes, query rewrites and schema adjustments. I start with measurements that show where the time actually goes, and only then change anything. Rewriting the application is a last resort, not a starting point.
PostgreSQL is where I go deepest and it is my default recommendation. A large part of the work, including data modelling, SQL, query optimization and data quality, carries over between engines. I also help with migrations to PostgreSQL or Supabase. In the first conversation I will give you an honest assessment of whether your case is a good fit.
It means turning manual checks into rules that run on their own: completeness (is anything missing), consistency (do invoice totals match the accounting), agreement between systems (do the CRM and the shop see the same customers). The rules run on a schedule, and every discrepancy triggers a notification saying exactly what disagrees and where.
Yes, and I start with a question surprisingly few companies can answer: how much data and how many hours of downtime can you genuinely afford to lose? I design the backup strategy to match, automate it and test restores in a scratch environment. You also get a short recovery procedure your team can follow without me.
Related services
Let's talk about your data
The consultation is free: you describe the problem, whether slow queries, reports that disagree or a planned migration, and I tell you where I would start and what effort to expect.
- Phone
- +48 573 021 012