Senior Data Integration Engineer (100% Remote)

Who We Are: Vori Health is an award-winning, nationwide, virtual-first, musculoskeletal medical practice focused on evidence-based care that treats the whole person. Using a unique care model to help patients find the best path forward, Vori Health connects patients to a trained care team that includes a nonoperative physical medicine physician, a health coach navigator, and a physical therapist who manage the initial patient assessment and then work to coordinate all aspects of care. We are on a mission to empower humanity to lead a healthier life. What You’ll Do: We are looking for a Senior Data Integration Engineer to design, build, and operate API-driven data services that connect operational systems, synchronize data reliably across boundaries, and land curated datasets in Snowflake while working closely with Hasura as the operational database and API layer . You will collaborate closely with Data Engineers and Implementation teams to ensure a seamless end-to-end data flow. Essential Functions: Infrastructure & Automation Own the design and improvement of data delivery pipelines across AWS (S3, Lambda, EventBridge , CloudWatch, etc.). Build and maintain integration platforms and services (REST/ GraphQL /event-driven) that expose and consume APIs safely, with clear contracts, versioning, and observability. Build Frontend react data management UIs Lead automation of ingestion, monitoring, and recovery processes — reducing manual effort and improving reliability. Build reusable infrastructure-as-code patterns (Terraform, CloudFormation) for consistent environment provisioning. Develop and maintain shared frameworks and scripts in Python and Bash for ingestion and pre-processing of third-party data files. Design and implement secure, scalable APIs in Node.js and Typescript to support our virtual care workflows Partner with Data Engineers to align ingestion mechanisms with warehouse needs and dbt transformations. Observability & Reliability Design and maintain alerting and observability frameworks for all data workflows. Implement metrics and dashboards to monitor latency, data freshness, file arrivals, and pipeline health. Perform root-cause analysis on failures and drive permanent improvements to prevent recurrence. Establish standards for logging, error handling, and notification integration (e.g., Slack , DataDog ). Define and enforce SLAs for ingestion timeliness and system uptime. Security & Compliance Oversee secure data exchange protocols (SFTP, HTTPS, AWS Transfer Family). Manage and rotate public/private keys for SFTP authentication with third parties. Partner with Security and IT to enforce least-privilege IAM roles, key policies, and encryption-at-rest/in-transit standards. Maintain audit trails and compliance documentation for all data integrations. Third-Party & Cross-Team Coordination Serve as the primary technical contact for external IT teams involved in data transfers. Coordinate with the Implementation team to onboard new partners, manage credentials, and troubleshoot issues. Track which third parties push vs. pull data, and document all mechanisms (SFTP, portals, secure email, APIs). Proactively manage external communication and escalation channels to minimize integration downtime. Communicate technical details clearly and diplomatically across internal and external teams. Continuous Improvement & Leadership Identify opportunities to streamline the data-ingestion lifecycle through automation, tooling, or process improvement. Lead technical reviews, mentor DataOps Engineers, and drive adoption of best practices. Contribute to the team’s long-term roadmap, with a focus on observability, security, and automation maturity. Partner with Data Engineers to align data-ingestion reliability with transformation and warehouse stability. Stay informed about new AWS and Snowflake features and advocate for practical adoption where appropriate . Supervisory Responsibilities None Perform other projects and duties as assigned Who You Are Required: Bachelor’s or Master’s degree in Computer Science , Engineering, or a related field. 5 + years of experience in data operations, with a strong background in building and optimizing data delivery pipelines and data management UI . Knowledge of Python, Typescript, bash , GraphQL , SQL Expertise working with AWS-based solutions Expertise working with modern data platforms (e.g., Redshift, Snowflake, etc.) and tools ( e.g. AWS S3, lambdas, etc.)