Senior Data Engineer, Octave

• Proficiency in SQL and Python with strong familiarity towards modern data engineering frameworks, infrastructure, and tooling
• Proficiency with data ops best practices, monitoring, pipeline automation, and CI/CD
• Experience with GCP or AWS data engineering tools, big data frameworks
• Experience with data modeling and medallion architecture
• A collaborative mindset, dependable execution, drive to reflect and improve, and humility to ask questions and learn
• Comfort using AI tools in day-to-day workflows, with a willingness to continuously rethink and improve how work gets done
• Curiosity and openness to experimenting with new tools and approaches; prior experience with AI tools is a plus
• Bachelor’s degree (or equivalent) in Computer Science, Data Science, Statistics, Engineering or a related field
• 5+ years of experience in data engineering, platform engineering, or ML engineering
• Experience working with major cloud data platforms and tools:
• Prolonged periods sitting at a desk and working on a computer
• Must be able to frequently communicate with others through virtual meeting applications such as Zoom and Google Meet
• Must be able to observe and communicate information on company provided laptop
• Move up to 10 pounds on occasion
• Must be eligible to work in the United States without sponsorship now or in the future

Desirable

• We’re looking for a Sr. Data Engineer with strong data platform experience to help evolve our modern data stack and contribute to the foundation of our emerging AI and ML platform
• This role sits at the intersection of data engineering, platform architecture and machine learning enablement and will bring high-quality, scalable, and ethical AI into real-world use
• You will partner closely with data scientists, analysts, and product managers to ensure our platform supports reliable data pipelines, scalable analytics, in addition to defining new architecture, best practices, and patterns for fellow engineers to inherit
• The ideal candidate is both a systems thinker and a hands-on builder who thrives in evolving environments and is passionate about creating reliable data infrastructure that enables peers and partner teams to move faster with data
• You will have the opportunity to learn and contribute to a machine learning enablement and will bring high-quality, scalable, and ethical AI into real-world use
• Design, build, and maintain scalable systems for ingestion, transformation, and storage of data, with a focus on testing and observability
• Implement frameworks, tooling, and automation to safely increase development velocity
• Develop foundational end-to-end AI/ML workflows from (1) source ingestion and preparation, (2) training and tuning, (3) experimentation and productionisation, and (4) downstream systems integration (EHR modules, micro-services, dashboards)
• Support iterative model development and production operations and observability (accuracy, drift, bias, fairness, reproducibility)
• Contribute to a culture of continuous improvement, knowledge-sharing and mentoring of peer engineers
• Leverage AI tools as a core part of daily work (drafting, research, iteration) to improve efficiency, quality, and decision-making