Senior Software Engineer, Data Platform

Medecision

Senior Software Engineer responsible for building and evolving cloud-native data services at Medecision. Focusing on data pipelines within a regulated healthcare environment to enhance clinical analytics.

Posted 6/12/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $130,000 - $155,000 per yearWebsite

Tech Stack

Tools & technologies

AirflowApacheBigQueryCloudDockerGoogle Cloud PlatformJavaMicroservicesPythonSQL

About the role

Key responsibilities & impact

Design, develop, and maintain production-grade Python and Java data services and pipelines deployed on Google Cloud Platform.
Build and evolve Google Cloud Dataflow batch and streaming pipelines for data ingestion, standardization, curation, and analytics load.
Implement and maintain event-driven data workflows using Google Cloud Pub/Sub.
Design and manage BigQuery datasets, table schemas, partitioning strategies, clustering, and reporting views.
Build and maintain Cloud Composer (Apache Airflow) DAGs for workflow orchestration.
Develop and maintain Cloud Run microservices and Cloud Functions.
Participate in design and code reviews; mentor junior engineers and contribute to shared coding standards.
Collaborate with teams to ensure on-time delivery and best engineering practices.
Engage proactively in the triage and resolution of escalated production issues.
Follow and comply with all security policies and procedures established by the organization, including adherence to HIPAA and HITRUST regulations.

Requirements

What you’ll need

Bachelor's degree in Computer Science, Software Engineering, Data Engineering, or equivalent practical experience.
5+ years of data engineering or backend software engineering experience building production data pipelines and platform services.
Proven hands-on experience with Google Cloud Platform data services: BigQuery, Cloud Storage, Cloud Pub/Sub, Cloud Dataflow, Cloud Composer, Cloud Run, Cloud Functions, Firestore, Cloud SQL, and Secret Manager.
Strong proficiency in Java for data pipeline development.
Proficiency in Python for Airflow DAG authoring and automation scripting.
Experience designing and implementing batch and streaming data pipelines.
Proficiency with BigQuery data modeling and SQL query optimization.
Experience with Apache Airflow / Cloud Composer.
Experience with containerization (Docker).
Proficiency with GitLab CI/CD for pipeline automation.
Excellent communication skills.

Benefits

Comp & perks

Remote work options
Professional development opportunities

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

PythonJavaGoogle Cloud PlatformBigQueryCloud DataflowCloud Pub/SubCloud ComposerCloud RunCloud FunctionsSQL

Soft Skills

communicationmentoringcollaborationproblem-solving

Certifications

Bachelor's degree in Computer ScienceBachelor's degree in Software EngineeringBachelor's degree in Data Engineering