A case study on designing production data infrastructure that moved the commercial needle.
The Problem
Gaming Innovation Group (GiG) is a B2B iGaming platform provider. Their business model depends on operators choosing GiG's platform to run their casino, sportsbook, or lottery products.
The challenge was simple to state, hard to solve: GiG wanted to go after larger, more established operators — the kind that already had thousands of active customers. But these operators wouldn't switch platforms unless they could bring their entire customer base with them. No one was going to tell 20,000+ players to re-register.
Without a migration path, GiG was limited to onboarding greenfield operators — new brands with zero customers. That's a smaller, slower market.
What I Built
I designed and delivered a comprehensive data migration framework that could ingest a source operator's full customer dataset — profiles, balances, transaction histories, consents, KYC records — validate it, transform it to fit GiG's data model, and load it into the live platform.
The key constraints were:
- Speed: The migration window had to be short. Operators can't afford extended downtime. We targeted under 30 minutes for a full migration of 20,000+ records.
- Accuracy: Financial data (balances, transaction histories) had to be perfect. A single cent off on a customer balance is a compliance and trust problem.
- Repeatability: This wasn't a one-off script. It needed to work across different source systems with different schemas, so it had to be configurable and extensible.
- Auditability: Every record needed a clear lineage — what came in, what was transformed, what went out. Regulators care about this.
The framework handled the full lifecycle: ingestion from the source operator's systems, schema mapping and validation, data quality checks, transformation to GiG's internal model, loading into production, and post-migration reconciliation to verify everything landed correctly.
The Outcome
The framework migrated 20,000+ customer records — including balances, consents, and profiles — in under 30 minutes.
More importantly, it changed GiG's commercial positioning. The company could now credibly pursue established operators as clients, a market segment that had previously been inaccessible. This opened a new revenue stream.
The project was highlighted multiple times in GiG's quarterly earnings calls, including the Q1 2024 earnings presentation, where leadership cited it as a key capability for attracting larger-scale clients.
What I Learned
Data engineering is a commercial function. This project didn't just move data — it unlocked a market segment. The migration framework was referenced in earnings calls not because of the technology, but because of what it enabled the sales team to do. That's the kind of impact I think about now whenever I'm building infrastructure: what does this make possible for the business?
Coordination matters as much as code. I co-ordinated this project end-to-end — requirements gathering with commercial stakeholders, technical design, development, testing, and client delivery. The hardest part wasn't the pipeline logic. It was aligning what the sales team promised, what the client expected, and what the data actually looked like.
Data quality is non-negotiable in financial systems. Migrating player balances isn't like migrating blog posts. Every record has regulatory and financial implications. Building robust validation and reconciliation into the framework from day one saved us from problems that would have been much harder to fix later.
I'm Julian Calleja, a Senior Data Engineer focused on real-time data platforms in iGaming. Currently building at Elantil, previously at GiG and SpinCity. Get in touch if you want to talk about data infrastructure or iGaming.