Director, Data and Platform
New
R
RxSenseHealthcare Technology
Remote-USFull-TimeDirector
Salary220,000 - 260,000 USD per year
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Job Details
- Experience
- 8+ years
- Required Skills
- ETLKafkaKubernetesNosqlSparkDevOps
Requirements
- 8+ years of experience architecting and building platforms in production.
- Proven, hands-on experience owning data architecture end to end, including ingestion, ETL, transformation, and BI layers.
- Proven, hands-on DevOps experience building, deploying, and operating production-scale infrastructure.
- Track record of writing and shipping production code.
- Depth in modern data stacks including distributed processing (Spark, Kafka), NoSQL (MongoDB, DynamoDB), data warehousing (Snowflake, Redshift, BigQuery), and transactional databases (Postgres, MySQL).
- Experience with PHI/PII handling and detection practices.
- Hands-on experience with DevOps tools, GitOps workflows, Kubernetes, and cloud infrastructure (AWS).
- Excellent communication and collaboration skills for translating architecture for technical and non-technical stakeholders.
- Prior experience building and leading a team, or clear readiness to take on direct reports.
- Ability to thrive in a small, fast-moving team environment.
Responsibilities
- Own the data architecture end to end, from the moment data lands in our systems through ETL and transformation, extracts, and the dashboards stakeholders rely on.
- Own devops and infrastructure for the AI engineering team end to end, including design and ownership of the platform architecture from ingestion through serving.
- Set technical direction and standards for data infrastructure, pipelines, ETL and transformation logic, and platform reliability.
- Build the systems and infrastructure you design, ensuring they are production-grade, deployable, observable, and stable.
- Write and ship production code personally.
- Build and lead the data and platform team, managing hiring and day-to-day direction.
- Mentor engineers on architecture, data design, devops, and platform thinking.
- Partner with AI engineering leadership to align platform investments with product and research priorities.
- Translate business and executive priorities into data strategy and architecture decisions.
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