Distributed Systems Developer
Ann Arbor, MI, United States
Toptal Member Since
April 29, 2022
Emiliano is a data engineer with expertise in distributed storage and event streaming systems. He's architected an aerospace-grade data acquisition, storage, and visualization system for petabytes of launch telemetry. Emiliano is focused on writing well-tested and clearly documented code that minimizes system complexity and technical debt.
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Go, Python, React, Redux, D3.js, Electron, CockroachDB, Kubernetes, MinIO...
CAD, Manufacturing, Geometric Dimensioning & Tolerancing (GD&T), ANSYS
ExperienceTest-driven Development (TDD) - 4 yearsTypeScript - 4 yearsPostgreSQL - 4 yearsReact - 3 yearsGo - 3 yearsDistributed Systems - 3 yearsKubernetes - 3 yearsFigma - 3 years
Linux, Kubernetes, GoLand, Visual Studio Code, Go, PostgreSQL
The most amazing...
...system I've built is a Raft consensus algorithm replicated time series database capable of ingesting over thirty million samples per second.
2020 - 2022
- Architected for petabyte scale data storage, analytics, and visualization for a platform built using Go, CockroachDB, Minio, React, and Redux.
- Led multi-site containerization effort with Kubernetes (VMware Tanzu), including implementing CI/CD pipelines using Argo CD, Tekton, Harbor, and Helm.
- Built WebAssembly and Electron-powered tools for performant analysis of vehicle telemetry.
Technologies: Go, Python, React, Redux, D3.js, Electron, CockroachDB, Kubernetes, MinIO, Django
2019 - 2021
System Integration Engineer
- Led the conceptualization, design, manufacturing, and testing of a modular autonomous vehicle prototype.
- Specialized in system integration and automotive powertrain design,. gearbox stress, and wear analysis. Worked on geometric dimensioning & tolerancing (GD&T) and automotive standards and regulations.
- Used Lean methodology to optimize the design and manufacturing process, focusing on reducing waste while promoting innovation.
Technologies: CAD, Manufacturing, Geometric Dimensioning & Tolerancing (GD&T), ANSYS
Arya Core is a high-performance time-series engine I created capable of writing 30 million samples per second on commodity hardware. It is built using Go, Minio, and gRPC. It runs as a set of homogeneous nodes that join together to form a cluster. Each node can read data from and send commands to data acquisition hardware, persist telemetry to storage, and distribute it to other nodes. The cluster exposes itself as a single data space, allowing users to query telemetry from anywhere in the cluster by connecting to a single node. Through this connection, a client can process real-time telemetry streams, perform closed-loop control, and query large quantities of historical data efficiently.
Developed a Redux state synchronization and declarative window management library for Electron apps. Allows users to maintain a single source of truth across multiple Node.js processes and fork new processes with ease.
Built an asynchronous, high throughput key value store for time series data. Caesium is embeddable into any Go program, and includes a concurrency friendly API for transferring large volumes of device data across a network.
Go, TypeScript, Python, C++
Test-driven Development (TDD), Database Design
2019 - 2022
Bachelor's Degree in Aerospace Engineering
University of Michigan - Ann Arbor, MI