C the Signs

Data Engineer

• Lead design and evolution of our cloud-native data platform built primarily on Google Cloud Platform.
• Inform strategic decisions around multi-cloud or AWS interoperability when needed.
• Establish data engineering best practices, coding standards, and architectural patterns.
• Build scalable ETL/ELT pipelines using dbt and Airflow.
• Develop ingestion pipelines for clinical and administrative data.
• Implement streaming and batch dataflows using Pub/Sub, Dataflow.
• Ensure HIPAA compliance and proper handling of PHI/PII across all pipelines.
• Provide oversight and technical direction for multi-cloud data integrations.

Lead Data Engineer

Cloud Engineer

• Lead day-to-day monitoring and management of GCP infrastructure, focusing on reliability, uptime, security, performance, and compliance
• Manage GKE clusters, including cluster lifecycle, node pools, workload deployment, and operational best practices.
• Implement and maintain GCP networking: VPCs, firewall rules, service networking, and private connectivity.
• Support data and application teams using GCP services such as BigQuery, Cloud SQL, Pub/Sub, Cloud Storage, Cloud Run.
• Own and maintain Terraform configurations for GCP and AWS using reusable modules, remote state, policy checks, and automation pipelines.
• Automate environment provisioning, scaling, and configuration with CI/CD tools such as Cloud Build, GitHub Actions, ArgoCD, or Jenkins.
• Build tooling and workflows that improve developer productivity (automated builds, deployments, secrets management, ephemeral environments).
• Build and enhance observability stacks using Cloud Monitoring, Prometheus/Grafana, ELK/Elastic, or OpenTelemetry.
• Lead incident response, troubleshooting, RCA generation, and post-incident improvement efforts.
• Define and manage SLOs, error budgets, and operational runbooks.
• Ensure secure configurations across cloud services, Kubernetes workloads, secrets storage, and network boundaries.
• Implement guardrails and compliance automation using IAM best practices, GCP Organization Policies, and Terraform checks.
• Work with security and compliance teams to meet HIPAA, HITRUST, SOC 2, or internal audit requirements.
• Maintain stability of a pre-existing AWS environment by performing tasks such as:
• Reviewing IAM roles and security posture
• Supporting workloads on EC2, ECS, EKS, RDS, S3
• Troubleshooting infrastructure or networking issues
• Managing configurations, upgrades, and patching
• Assist teams that rely on AWS-hosted systems and ensure smooth integration with GCP-centric operations.
• Make small-to-medium improvements or automation updates for AWS infrastructure using Terraform or CI/CD workflows.
• Mentor DevOps, CloudOps, and Platform Engineers through pair programming, reviews, and best-practice sharing.
• Partner with development, data, and security teams to build highly reliable, cloud-native applications and pipelines.
• Establish operational standards, documentation, and playbooks for cloud operations.

Lead CloudOps Engineer

Social Media Manager

• Help build a global movement for early cancer detection
• Capture moments at events and amplify the founder's story
• Engage audiences through social content
• Transform the mission into inspiring creativity

Social Media & Community Growth Manager

Machine Learning Engineer

• Clean, transform, and prepare large, complex healthcare datasets for machine learning model development (missing values, outlier detection, feature engineering, normalization).
• Identify, collect, and curate relevant industry-specific datasets and format data for LLM training pipelines.
• Design, train, and fine-tune various LLMs on extensive healthcare data to solve clinical or operational problems.
• Set up and manage training environments, including GPU instances and required software; optimize hyperparameters and memory usage.
• Integrate structured and unstructured data for multi-modal/multi-input models.
• Evaluate model performance using appropriate metrics and implement optimization strategies.
• Develop and maintain robust, scalable data and ML pipelines for training, inference, and deployment.
• Collaborate with data scientists, clinicians, and software engineers to integrate models into production and ensure data privacy and security compliance.
• Stay up-to-date with advancements in machine learning and healthcare AI and explore new technologies.
• Maintain clear documentation of models, data pipelines, and experimental results.

• Collaborate with data scientists and machine learning engineers to understand data requirements for LLM and machine learning model fine-tuning.
• Design, build, and maintain scalable data pipelines to ingest, process, and store massive and diverse healthcare datasets.
• Implement robust data validation and monitoring to ensure the integrity, accuracy, and consistency of all training datasets.
• Implement robust data cleaning, validation, and transformation processes to ensure data quality and integrity.
• Develop and optimize data structures and schemas for efficient access and utilization by LLMs and machine learning models.
• Work with the team to identify and acquire new data sources, ensuring compliance with relevant healthcare regulations (e.g., HIPAA).
• Monitor data pipeline performance, troubleshoot issues, and implement optimizations to improve efficiency and reliability.
• Document data engineering processes, data models, and data dictionaries.
• Stay up-to-date with the latest advancements in data engineering, big data technologies, and machine learning.

Lead Data Engineer

Lead CloudOps Engineer

Social Media & Community Growth Manager

Machine Learning Engineer

AI Data Engineer