Nodes

whoami

I’m a Staff-level Data & Distributed Systems Engineer operating at the intersection of large-scale data infrastructure and systems architecture. My work focuses on the patterns that make data platforms reliable, observable, and horizontally scalable.

The Vector Vombat persona is a nod to two things:

1. Vector — the fundamental unit of direction and magnitude in systems thinking. Data pipelines, event streams, and distributed consensus all reduce to vectors of state change propagating through a system.

2. Vombat — the wombat (Vombatus ursinus), native to Australia. An animal that builds complex, resilient burrow systems, engineers cubic fecal markers for territory mapping (a genuine unsolved geometry problem), and survives environmental extremes through metabolic efficiency. Systemic durability in its purest biological form.

cat /etc/expertise.d/*

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distributed-systems/
├── consensus/          # Raft, Paxos, CRDTs
├── storage-engines/    # LSM trees, B-trees, write-ahead logs
├── stream-processing/  # Kafka, Flink, exactly-once semantics
└── coordination/       # ZooKeeper, etcd, distributed locks

data-engineering/
├── orchestration/      # Airflow, Dagster, Prefect
├── warehousing/        # Snowflake, BigQuery, Redshift
├── lakehouse/          # Delta Lake, Iceberg, Hudi
└── quality/            # Great Expectations, dbt tests, schema evolution

infrastructure/
├── kubernetes/         # Operators, StatefulSets, service mesh
├── observability/      # Prometheus, Grafana, OpenTelemetry
├── iac/                # Terraform, Pulumi, ArgoCD
└── networking/         # Service discovery, load balancing, mTLS

uptime

My career has been a progression through increasing levels of system complexity:

• Data Platform Architecture — Designing end-to-end data platforms processing billions of events daily, with focus on exactly-once delivery guarantees and schema evolution strategies.

• Distributed Storage — Building and operating distributed databases (Cassandra, ScyllaDB, CockroachDB) across multi-region deployments with tunable consistency.

• Stream Processing — Real-time event processing pipelines with Kafka Streams and Apache Flink, handling backpressure, late-arriving data, and watermark management.

• Platform Engineering — Internal developer platforms with self-service data infrastructure, Kubernetes operators for stateful workloads, and GitOps-driven deployment pipelines.

dig vectorvombat.dev

This site is built with the same principles I apply to production systems:

nslookup vectorvombat.*