100% Remote, USA
Six Feet Up is seeking a Senior Data Engineer with deep experience designing, building, and maintaining secure, scalable data systems.
In this role, you will work with cross-functional teams to turn complex data challenges into reliable production solutions. You will design data pipelines, build processing workflows, improve data quality, support machine learning initiatives, and help clients make better use of structured, unstructured, time-series, sensor-based, and high-volume data.
We are looking for someone who can bring technical leadership, sound engineering judgment, and strong communication skills to ambiguous data problems. The ideal candidate is comfortable working across data engineering, cloud infrastructure, machine learning support, and production software delivery.
As a Senior Data Engineer, you will:
- Design, build, and maintain robust, scalable data pipelines
- Develop ETL/ELT workflows for collecting, transforming, validating, and storing data
- Work with cloud-based data processing and storage systems
- Implement data validation, quality checks, monitoring, and transformation workflows
- Process complex datasets, including noisy, high-volume, time-series, sensor, or device-generated data
- Support machine learning workflows, including data preparation, model training, evaluation, and production integration
- Collaborate with data scientists, researchers, software engineers, and client stakeholders
- Translate prototype data workflows into reliable, maintainable production systems
- Create systems that are well-documented, testable, secure, and ready for audit or review
- Communicate technical tradeoffs clearly to both technical and non-technical audiences
If you are a motivated Senior Data Engineer seeking a challenging and meaningful role, we encourage you to apply.
We are looking for someone with strong hands-on experience in:
- Data pipeline architecture and implementation
- ETL/ELT orchestration tools such as Airflow, Dagster, or similar platforms
- Python-based data engineering and data processing tools
- Cloud-based data infrastructure, storage, and processing
- Data modeling, schema design, validation, and quality-control practices
- Working with public, proprietary, structured, and unstructured datasets
- Time-series, sensor, IoT, or other high-volume data sources
- Supporting machine learning or data science teams with reliable data workflows
- Building reproducible, testable, and maintainable data systems
- Version control, automated testing, and collaborative software development practices
Strong candidates may also have experience with:
- Machine learning pipelines for classification, prediction, recommendation, or categorization systems
- MLOps, model evaluation, experiment tracking, and reproducible ML workflows
- Processing noisy signal data or other data that requires cleaning, filtering, or feature extraction
- Healthcare, digital health, research, or regulated software environments
- HIPAA, privacy-preserving data architecture, or secure cloud data processing
- Working with sensitive, clinical, or user-generated data
- Helping researchers or domain experts scale early-stage algorithms into production-ready systems
- Designing systems that support thousands or more users
A Plus:
- Experience with containers, CI/CD, DevOps practices, or Kubernetes
- Familiarity with AWS, Google Cloud, Azure, or similar cloud platforms
- Experience with consumer analytics, dashboards, or data visualization products
- Experience supporting FDA, SaMD, clinical validation, audit, or regulatory documentation efforts
- Experience designing secure data workflows for privacy-sensitive applications
About You
You are a senior engineer who brings structure to ambiguous technical challenges. You ask thoughtful questions, identify risks early, and know how to balance research needs, business goals, engineering quality, and long-term maintainability.
You care about data quality, privacy, testing, documentation, and clear communication. You are comfortable designing architecture, writing production code, reviewing data workflows, and collaborating with people from different technical backgrounds.
You enjoy helping clients move from ideas and prototypes to secure, scalable, production-ready systems.