Senior Data Engineer - Remote (USA)

About the Role

Six Feet Up is looking for a Senior Data Engineer with extensive experience in designing, building, and maintaining secure, scalable data systems. You will collaborate with cross-functional teams to transform intricate data challenges into reliable production solutions, focusing on data pipelines, processing workflows, data quality, and supporting machine learning initiatives. This role requires technical leadership, sound engineering judgment, and strong communication skills to tackle ambiguous data problems, spanning data engineering, cloud infrastructure, machine learning support, and production software delivery.

Responsibilities

• Design, build, and maintain robust, scalable data pipelines.
• Develop ETL/ELT workflows for data collection, transformation, validation, and storage.
• 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 well-documented, testable, and secure systems ready for audit.
• Communicate technical tradeoffs clearly to both technical and non-technical audiences.

Requirements

• Strong Hands-on Experience:
• Data pipeline architecture and implementation.
• ETL/ELT orchestration tools (e.g., Airflow, Dagster).
• Python-based data engineering and processing tools.
• Cloud-based data infrastructure, storage, and processing.
• Data modeling, schema design, validation, and quality control.
• 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 (classification, prediction, recommendation, categorization).
• MLOps, model evaluation, experiment tracking, reproducible ML workflows.
• Processing noisy signal data requiring cleaning, filtering, or feature extraction.
• Healthcare, digital health, research, or regulated software environments.
• HIPAA, privacy-preserving data architecture, secure cloud data processing.
• Working with sensitive, clinical, or user-generated data.
• Scaling early-stage algorithms into production-ready systems for researchers.
• Designing systems supporting thousands of users.
• A Plus:
• Containers, CI/CD, DevOps practices, or Kubernetes.
• AWS, Google Cloud, Azure, or similar cloud platforms.
• Consumer analytics, dashboards, or data visualization products.
• Supporting FDA, SaMD, clinical validation, audit, or regulatory documentation.
• 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 balance research needs, business goals, engineering quality, and long-term maintainability. You prioritize data quality, privacy, testing, documentation, and clear communication. You are comfortable designing architecture, writing production code, reviewing data workflows, and collaborating with diverse technical backgrounds. You enjoy helping clients transition from ideas and prototypes to secure, scalable, production-ready systems.