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.
Restrictions
Telecommuting is OK
No Agencies Please
Requirements
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 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 techn