Senior Solutions Engineer

source{d} · Jun 3rd 2019

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Location: Madrid / Fully remote

Seniority: Senior/Expert

Compensation: 49,000€ to 53,000€ + 0.1% stock options

At source{d} we are building the data platform that enables engineering leaders & teams to use source code as data for getting insights on their people, processes and technology—as well as feeding sophisticated Machine Learning on code algorithms which power the next generation of developer tooling, such as assisted code review. We are an open-core company built around our Open Source projects. We have raised over 10million USD so far, and we are currently in an exciting stage of growth.

Role

The Solutions Team leads the implementation of source{d} at customers, building solutions based on source{d}, developing custom features and integrating with other platforms.

The underlying stack is developed primarily in Go, with some Scala and Python. Custom features and integration code often relies on Python. Most use cases require extensive use of SQL.

Responsibilities

  • As a Solutions Engineer, you will design and build solutions based on source{d}, the data platform for your software development lifecycle.

  • You will be heavily involved in project management for customer projects.

  • You will be involved in the definition, planning, and delivery of solutions for our prospects and customers.

  • You will develop demos and solutions that can be reused across different customers.

  • You will work closely with the rest of the engineering team, who will enable you to deliver demos and projects, both by means of internal support as well as the development of new features.

Requirements

  • You will code primarily in Python, SQL and Go. Previous experience with Python and SQL is preferred. Previous experience with Go is not a strict requirement; we strongly believe that it can be learned easily by any skilled developer. Experience with other languages is a plus.

  • Previous experience in consulting projects or professional services.

  • (Optional) Experience in analytics projects in industries such as banking, professional services, consultancy, etc.

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