Senior Software Engineer, Data Platform

Medecision

Location: US
Workplace: Remote
Employment: Full Time
Salary: —

Posted 3mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

Responsibilities

Design, develop, and maintain Python and Java data services and pipelines on Google Cloud Platform
Build and evolve Google Cloud Dataflow batch and streaming pipelines
Implement and maintain event-driven data workflows using Google Cloud Pub/Sub
Design and manage BigQuery datasets, table schemas, partitioning strategies, 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
Collaborate with on-shore and off-shore teams, architects, and tech leads
Contribute to CI/CD pipeline improvements using GitLab CI/CD
Engage proactively in the triage and resolution of escalated production issues
Follow and comply with all security policies and procedures
Own and evolve the end-to-end data ingestion pipeline
Design and implement custom dataset ingestion capabilities
Maintain and improve the Ingestion Event Service (IES)
Implement FHIR R4 data ingestion workflows via Pub/Sub and GCP Healthcare Datasets
Support population matching data flows
Build and maintain reporting dataset views
Integrate with third-party clinical analytics engines
Ensure all data services meet HIPAA requirements
Use Claude Code as a primary productivity tool for code drafting, refactoring, test generation, and technical documentation
Leverage AI-assisted workflows to accelerate implementation, surface edge cases, generate structured artifacts, and conduct at-scale analysis
Contribute to building and exposing MCP-wrapped APIs
Maintain strict HIPAA discipline in all AI-assisted work
Contribute to the team's shared AI knowledge base

Requirements

5+ years of data engineering or backend software engineering experience
Proven hands-on experience with Google Cloud Platform data services
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
Experience with Apache Airflow / Cloud Composer
Experience with containerization (Docker)
Proficiency with GitLab CI/CD for pipeline automation
Excellent communication skills
Familiarity with Datadog for service monitoring, alerting, and observability
Familiarity with Sisense or equivalent BI/reporting platforms
Solid understanding of AI concepts, capabilities, and limitations
Hands-on experience with Claude Code or equivalent AI-assisted tools
Ability to evaluate AI-generated code critically
Practical understanding of MCP (Model Context Protocol) or strong willingness to learn
Commitment to responsible AI use
HIPAA discipline in AI-assisted work
Openness to contributing to and learning from a shared AI knowledge base

Preferred

Knowledge of HIPAA and experience working in HIPAA-regulated product environments
Hands-on experience with HAPI FHIR R4 and healthcare interoperability standards
Understanding of multi-tenant SaaS architecture patterns

Skills

Python
Java
Google Cloud Platform
BigQuery
Cloud Storage
Cloud Pub/Sub
Cloud Dataflow
Apache Beam
Cloud Composer
Apache Airflow
Cloud Run
Cloud Functions
Firestore
Cloud SQL
PostgreSQL
Secret Manager
Docker
GitLab CI/CD
Datadog
Sisense
Claude Code
HAPI FHIR R4
HL7
FHIR

Responsibilities

Requirements

Preferred

Skills

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