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Job Responsibilities:
The Field Engineer acts as the bridge between engineering, operations, commercial, and quality teams, leading the design and delivery of scalable technical solutions that make processes smarter, faster, and more efficient. The role requires ownership of initiatives from end to end, influencing cross-functional teams and supporting collaborators through technical guidance.Responsibilities include developing automations and integrations using Python and JavaScript, improving data and workflow quality, and advising both technical and non-technical teams. The Field Engineer serves as a subject-matter expert in operational efficiency through technology and makes day-to-day technical decisions aligned with company strategy.
Act as a technical advisor and liaison between engineering, operations, and customer-facing teams.
Design and build technical solutions, including internal tools, scripts, and automations, using Python and JavaScript.
Collaborate with both highly technical stakeholders and non-technical users to identify pain points and translate them into actionable engineering tasks.
Troubleshoot and optimize platform integrations to ensure smooth data flows.
Build scalable, self-serve solutions for common workflows to reduce manual overhead.
Proactively identify issues, propose solutions, and independently lead high-visibility projects to implement them end to end.
Contribute to data quality and consistency through programmatic checks and thoughtful system design.
Share best practices and provide technical guidance and support to peers and cross-functional collaborators.
Additional Job Details:
- Technical experience in Python, JavaScript, or another relevant language for automations, integrations and scripting.
- Strong problem-solving skills with the ability to plan and execute complex technical solutions.
- Excellent communication and collaboration skills, with the ability to work across multiple teams.
- Curious and self-driven, with a strong desire to learn and adapt to new technologies and challenges.
- Experience working with APIs, data pipelines, and automation frameworks.
- Customer success mindset, with a passion for helping internal teams and customers succeed.
- Ability to translate operational concepts into actionable solutions for both technical and non-technical stakeholders.
- Experience with cloud platforms (AWS, GCP, or Azure) and data processing tools is a plus.
- 2+ years of engineering experience, ideally in a client-facing setting.
- Curiosity and desire to learn
- Bachelor's degree with an engineering or analytics focused field (e.g., Computer Science, Engineering, Mathematics, Statistics) or equivalent work experience.
- Hands-on experience in ML lifecycle applications, data management, and data wrangling.
- Python Experience with C# is a plus.
- Understanding of NLP concepts and techniques would be a plus.
- Passion for AI and ML technologies, with a history of exploring new concepts and technique.