> Markdown version of [/jobs/ext/200785-sr-data-engineer](https://www.wearedevelopers.com/jobs/ext/200785-sr-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Engineer - **Company:** OCTAVE LLC - **Location:** Nashville, TN, United States (Remote available) - **Experience:** Expert - **Salary:** $142,600.0 - $176,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Computing Platforms, Big Data, BigQuery, Continuous Integration, Information Engineering, Data Infrastructure, Data Warehousing, Python (Programming Language), Machine Learning, Cloud Services, Tensorflow, SQL Databases, Systems Integration, Web Services, EHR Systems, Pytorch, Delivery Pipeline, Large Language Models, Apache Spark, Scikit Learn, Information Technology, Machine Learning Operations, Data Pipelines, Google Meet, Microservices - **Published:** May 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d0cc97d0b234ff83 ## About the Role Do you have experience in SQL databases?, * 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. * Knowledge of modern compute and ML frameworks/libraries (i.e., Spark, TensorFlow, PyTorch, scikit-learn). * Ability to build production APIs and services, inclusive of MCP servers that expose internal data/services to LLMs. * 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: * Preferred experience: * + Healthcare, behavioral health, EHR systems, and/or regulated industries. + Specific expertise with: AWS/GCP, dbt, AirflowAirbyte, Redshift/BigQuery., * 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. ## Description 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, and production ready machine learning systems 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., * 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 productionization, 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., As part of our hiring process, we may use technology tools, including AI-supported systems, to assist with reviewing applications or documenting interviews. These tools are designed to support our team, not replace human judgment, and final hiring decisions are always made by our team. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Shipping Faster with Less: Render on Cloud Hosting, AI Workloads, and the Future of DevOps](https://www.wearedevelopers.com/videos/1894-shipping-faster-with-less-render-on-cloud-hosting-ai-workloads-and-the-future-of-devops) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Making Data Warehouses fast. 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