Data Pipeline Development & Maintenance: Work across a mixed-maturity pipeline environment
Data Modeling: Build and optimize data models that serve a diverse set of consumers. You'll make the data accessible and trustworthy, not just available
Simulation Data Integration: Work within the in-house simulation suite to add data-capturing capabilities and ensure simulation outputs feed cleanly into downstream pipelines alongside real-world field data
Data Quality & Observability: Instrument pipelines with quality checks, anomaly detection, and alerting so issues surface early
Cross-Functional Data Support: Translate ambiguous asks into well-defined requirements, repeatable datasets and lightweight Dashboards that the team can use independently going forward
Data Platform Infrastructure Contribution: Improve the features and reliability of our internal data platform over time
Documentation: Own the technical documentation for pipelines, data models, and schemas you touch. In a team this cross-functional, good documentation is a force multiplier

3+ years of industry experience as a Data Engineer in a startup or fast-moving environment.
Strong proficiency in Python and SQL, with hands-on experience building production-grade data solutions.
Experience designing and maintaining data pipelines and data models/warehouses that process large, structured scientific or engineering datasets.
Hands-on experience building on AWS (e.g., S3, ECS, Lambda, IAM) combined with CI/CD and containerization (e.g., GitHub Actions or CircleCI, Docker) to automate, deploy, and maintain data and ML workloads in the cloud.
Practical MLOps experience: setting up and operating MLOps frameworks (e.g., MLFlow, DVC)

Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions
Retirement savings with company matching
Paid parental leave
Inclusive family-building benefits
Flexible paid time off
Company-wide seasonal breaks
Support for flexible work arrangements that enable sustainable performance
Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs

Data Engineer

Key skills