Trading Infrastructure Engineer · Zürich, Switzerland

I will run the cloud infrastructure your company can rely on.

Over nine years across regulated crypto, banking and ETP issuers, I build and run the systems that stay up while the market is live, without anyone holding them up by hand.

10 examples 93 tests

Infrastructure and Observability

These are the 13 tools I actually reach for to build and run trading infrastructure. They come from real production work, not a wishlist. Where a tool has a tested example you will find it on the card, along with how deep I go.

Infrastructure as Code

Infrastructure I can reproduce and review. Nothing is held up by hand.

Terragrunt

How I keep Terraform DRY. One provider and one set of conventions, reused across every component. Here it stands up a VPC, a security group, a transit gateway and the EC2 nodes from the most widely used registry modules.

Advanced
Example VPC, security group, transit gateway and EC2 on LocalStack ✓ 8

Terraform

The foundation underneath. How I describe and version cloud infrastructure, used to provision real production infra.

Advanced

Cloud and Compute

Where trading systems run, and how they scale while the market is live.

AWS

My main cloud across every role. Networking, IAM, and keeping the bill sane for trading infrastructure.

Production owner
Example S3 and DynamoDB on LocalStack ✓ 5

Kubernetes

Runs the trading and venture builder workloads. I ran EKS in production while trades were live.

Production owner
Example deploy and scale on minikube ✓ 4

Amazon EKS

I designed the EKS and Fargate setup across a whole venture builder portfolio.

Advanced
Example the Kubernetes layer on minikube ✓ 4

AWS Fargate

Serverless containers. It took node management off my plate on the EKS platform.

Advanced

Software Engineering

These are real projects I have written, with working examples locally tested on LocalStack, Postgres and Minikube.

Software Engineering

The trading systems I build, from the matching engine to market data and P&L. Each one is a real example with a test suite behind it.

Hyperliquid Markets Crawler

I crawl the live Hyperliquid markets into Postgres. It keeps the latest state with idempotent upserts and a snapshot history that only ever grows. One of the tests hits the real API.

Production owner
Example Python and Postgres ✓ 20

Limit Order Book

A continuous matching engine with price and time priority. Limit and market orders, partial fills, cancels, and trades that print at the resting price. The kind of core I have built on the exchange side.

Production owner
Example price and time priority matching ✓ 12

OHLCV Candle Aggregator

I resample a raw trade stream into fixed interval candles with a volume weighted average price. This is the heart of the market data platform I run, turning ticks into bars.

Production owner
Example ticks into OHLCV bars with VWAP ✓ 12

Position and P&L Engine

From a stream of fills I track the net position, the weighted average entry, and realized and unrealized P&L, including a clean flip from long to short. The accounting a trading desk relies on.

Production owner
Example weighted average cost and mark to market ✓ 18

More Infrastructure

The rest of the stack that keeps trading systems shipping, observable and affordable.

CI/CD and Automation

A solid lifecycle so changes ship safely and often.

CI/CD Pipelines

I automate the whole path from commit to production. Here, GitHub Actions runs every example test suite on each push.

Advanced
Example GitHub Actions workflow

Feature branch environments

A throwaway environment for every branch, so every change can be reviewed on its own.

Advanced

Observability

Monitoring as code, because you cannot run what you cannot see.

OpenTelemetry

Traces, metrics, and logs I own across the services, portable to any backend.

Advanced
Example spans via an in memory exporter ✓ 4

Prometheus

Collects the metrics and drives the alerts for production trading systems.

Advanced
Example the exposition format ✓ 3

Grafana

Dashboards for the health of the systems and the trading on top of them.

Advanced
Example provisioned dashboards on minikube ✓ 7

FinOps and Cost

Reliability and efficiency are the same discipline.

AWS Budgets

Guardrails that keep cloud spend predictable.

Proficient

Cost Anomaly Detection

I used anomaly analysis to cut cloud cost across a portfolio of projects.

Proficient