Senior Software Engineer

Summary

Join Vendelux, a Series A SaaS company, as a Senior Software Engineer - Data and play a crucial role in enhancing the quality and efficiency of our data infrastructure. You will develop and maintain data pipelines, integrate new data sources, and collaborate with data scientists to implement scalable machine learning models. This role requires extensive experience with data pipelines, workflow management tools, and cloud-based infrastructure. You will also contribute to a collaborative engineering culture and participate in on-call rotation. Vendelux offers a remote-first work environment and values diverse backgrounds.

Requirements

• Minimum of 6 years of relevant engineering experience and exposure to working with data, data pipelines and/or machine learning
• Expert level knowledge of python
• Track record of shaping and shipping valuable features
• Track record of driving high-leverage improvements to infrastructure and process
• Judgment to take on technical debt and risk where appropriate
• Strong communication skills, especially written
• Previous startup experience

Responsibilities

• Develop, release, and maintain high quality data pipelines, ETL and ELT processes
• Own and guide the development of our data infrastructure
• Develop custom integrations and APIs to automate our data collection, cleaning and enrichment pipelines
• Promote a culture of collaboration and learning across engineering, product, and design team via mentoring, documentation, presentations, or other knowledge-sharing methods
• Ensure our data is always available by participating in our on-call rotation
• Work with stakeholders including data-ops, product and executives and assist them with data-related technical issues
• Determine where in our infrastructure we should host data based on the use case and data model
• Collaborate with Data Scientists in order to design scalable implementations of their models
• Identify bottlenecks and implement improvements to our data and engineering processes, and tools

Preferred Qualifications

• DevOps or platform/infrastructure experience (or deep interest)
• Experience with ML Ops processes and designing/building/deploying/productizing ML models