Connect the Systems Your Business Already Runs On
Most companies do not need a new platform. They need the platforms they already pay for to share data reliably: the CRM with the billing system, the legacy database with the new API, the SaaS tool with the warehouse. I design and build those connections in Python, with idempotent writes, replayable flows and phased cut-overs, so the integration keeps working long after launch.
What Problems I Solve
Third-Party API Integrations
Payment processors, auth providers, CRMs, ERPs, messaging and analytics tools. I handle authentication, rate limits, retries and webhook delivery so your team does not have to.
System-to-System Data Sync
Keep two or more systems of record consistent: one-way feeds, two-way sync, or a migration from one platform to another with validation at every step.
Legacy System Modernization
Put a clean API in front of an old database or monolith so new products can use it, then move pieces out gradually instead of a risky big-bang rewrite.
Event-Driven Workflows
Replace nightly batch jobs and polling with events over Kafka, RabbitMQ or Celery, so downstream systems react in seconds and failures are retried, not lost.
Platform and Cloud Migrations
Move a platform between clouds or between SaaS vendors with a phased plan, dual-running where needed and a rollback path at each stage.
Integrations That Keep Breaking
Audit an existing integration that fails silently, duplicates records or drifts out of sync, then fix the root cause and add the monitoring that was missing.
Value I Deliver
Zero Data Loss Cut-Overs
Phased validation across environments before production. The OneTrust migration moved 20+ enterprise clients with zero data loss and zero production incidents.
Idempotent and Replayable
Every write can be retried safely and every batch can be replayed. A failed run is a re-run, not a data clean-up project.
Visible Failures
Dead-letter queues, alerts and dashboards on every flow. You find out from a metric, not from a customer.
Documented Contracts
OpenAPI specs, schema definitions and mapping tables your team can read, so the integration outlives the engagement.
Less Manual Work
Spreadsheet exports, copy-paste between tools and manual reconciliations go away once the systems talk directly.
Security at the Boundary
Secrets managed properly, least-privilege credentials per system, input validated at the edge, audit trail on sensitive data.
Real-World Implementations
Cross-Platform Compliance Data Migration
Challenge
After OneTrust acquired Convercent, compliance records for 20+ enterprise customers had to move between two SaaS platforms with different data models: 100+ custom fields, 50+ data types and strict privacy rules. Any loss or corruption would be a compliance incident for the customer.
Solution
I owned the migration end to end, from design to production cut-over:
- Mapping engine that transforms records between the two schemas, driven by configuration rather than one-off scripts
- Django REST endpoints on Kubernetes with idempotent writes, schema validation and transactional rollback
- Phased validation across DEV, QA1, QA2 and PROD, each stage signed off before the next
- Parallel batch processing for throughput without sacrificing ordering guarantees
- Reconciliation reports comparing source and target counts per client and per data type
Results
Every client moved with zero data loss and zero production incidents. The configuration-driven mapping meant each new client was a config change, not a new project.
Technologies Used
Legacy Platform Migration Between Clouds
Challenge
A bioanalytical platform running on Azure had grown expensive to operate and hard to extend. The business wanted to move it to AWS, improve its security posture and speed up ML inference, without interrupting the labs that depended on it.
Solution
- Designed REST APIs and microservices that wrapped the legacy components so they could be moved one at a time
- Rebuilt the infrastructure on AWS with Docker and infrastructure as code
- Hardened authentication, secrets handling and network boundaries during the move rather than after
- Ran old and new side by side until each service was verified, then cut over
Results
The platform ran on AWS with 35% less operational overhead, a stronger security posture and lower inference latency, with no interruption to the labs using it.
Technologies Used
High-Throughput Media Migration Across Microservices
Challenge
Thousands of media records a day had to move between microservices and into Firebase for one of Brazil's largest media companies, while the products reading that data stayed online.
Solution
- Built a migration pipeline on Django REST Framework that pulled from the source services and wrote to Firebase in batches
- Made every write idempotent so partial failures could be retried without duplicates
- Kept the old read path live until the new one was verified record by record
Results
The migration ran daily with zero downtime for the products depending on the data.
Technologies Used
Technologies & Tools I Work With
Integration Layer
Protocols & Contracts
Messaging & Events
Data Stores
Cloud & Infrastructure
Observability
How I Work
Map the Systems
Which systems, which data, which direction, how often, and what happens today when it fails. I read the existing code and the vendor docs before proposing anything.
Design for Failure First
Every integration fails at some point: rate limits, timeouts, schema changes on the other side. I design retries, idempotency, dead-letter handling and alerts before writing the happy path.
Build With Replay in Mind
Flows are built so any batch or event can be re-run safely. Tests cover the contract with each external system, with recorded responses so the suite does not depend on the vendor being up.
Cut Over in Phases
Dual-run, compare, then switch. Each stage has a go/no-go check and a rollback path. Nobody finds out about the migration from a broken report.
Hand Over With Monitoring
Dashboards, alerts, runbooks and a mapping document your team can read. I stay available after launch for the first weeks of real traffic.
How We Can Work Together
Integration Review
A short, fixed-scope look at an existing or planned integration. You get a written report: risks, failure modes, what to fix first and a plan you can execute with or without me.
Fixed-Scope Project
A defined integration or migration with a written scope, timeline and deliverables. Best when the systems and the goal are already clear.
Monthly Retainer
Ongoing ownership of your integrations: new connections, vendor API changes, monitoring and fixes, with predictable monthly cost and priority response.
Not sure which fits? See how consulting engagements work or book a call.
Frequently Asked Questions
Which systems can you integrate?
Anything with an API, a database or a file export: SaaS tools (CRM, ERP, billing, support desks), payment providers, auth providers, internal services and legacy databases. If a vendor has no API, I work from exports, webhooks or a database replica, whichever is safest.
Will the integration break when the vendor changes their API?
It will change, so the integration is built to notice. Contract tests with recorded vendor responses, schema validation at the boundary and alerts on unexpected payloads mean you find out from a failing check, not from missing data weeks later.
How do you avoid downtime during a migration?
Phased cut-over: the new path runs alongside the old one, results are compared, and traffic moves only when the numbers match. Each phase has a rollback. This is how the OneTrust migration moved 20+ clients with zero production incidents.
Can you work inside our existing codebase and team?
Yes. Most integration work lives inside an existing system. I follow your repo's conventions, open pull requests your team reviews, and document decisions where your team will find them.
How long does an integration take?
A single third-party API integration is typically a few weeks. A multi-system migration with validation phases is typically a few months. I give a written estimate after the first call, once I have seen the systems involved.
Have Two Systems That Need to Talk?
Tell me which systems and what data, and I will tell you the safest way to connect them.