7 days ago
Base Salary
$166k - $243k/yr
Responsibilities
- Lead and mentor a data engineering pod, prioritizing workload and driving on-time delivery.
- Set technical direction and standards for EDW pipelines, data models, schemas, batch and streaming architectures, and AI/RAG data infrastructure.
- Architect scalable data solutions on cloud platforms and translate business and clinical stakeholder needs into technical roadmaps.
- Own pipeline SLAs/SLOs, operational metrics, uptime, MTTR, data-quality reporting, and recovery plans when KPIs are missed.
- Lead root-cause analysis and mitigation for complex pipeline and data-quality issues and participate in on-call escalation.
- Define source-management, version-control, QA/testing, documentation, SOP, escalation, and AI-assisted code contribution standards.
- Set standards for embedding strategies, vector-store selection, corpus curation, and LLM/RAG data architecture.
- Coordinate with data science, security, and compliance teams to ensure platform readiness and enforce security and privacy standards.
- Present technical plans and operational metrics to stakeholders and leadership and contribute cost and budget input for cloud and AI/vector-database usage.
Requirements
- Bachelor's degree in Computer Science or a related technical field, or equivalent hands-on experience.
- 8–12 years of experience in technology with significant data-centric leadership.
- 6–8 years of hands-on experience architecting data solutions on a cloud platform.
- At least 2 years of formally leading engineers or technical workstreams.
- Extensive healthcare-domain experience, including EMR/EHR experience with Epic and/or Cerner.
- Experience partnering with healthcare providers, clinical operations teams, or healthcare organizations.
- Understanding of HIPAA, HL7, and FHIR healthcare data standards and compliance frameworks.
- Expert-level SQL, data modeling, and semantic-layer design experience.
- Experience with Spark, Airflow, Databricks, and/or Snowflake for batch and streaming architectures.
- Experience setting standards for LLM/RAG data architecture at scale, including embedding strategy, vector-store selection, and corpus curation.
- Preferred Cloud Professional Data Engineer or ML Engineer certification.
- US citizenship is required.
Benefits
- Compensation may include annual bonus or other incentive compensation, equity awards, and an Employee Stock Purchase Plan (ESPP).
- Benefits information is available through Rackspace Technology.
Tech Stack
Categories
Data Engineering
About Rackspace
Rackspace provides managed cloud and IT services for enterprises, including multicloud operations, cloud migration, private cloud, managed security, and application/platform management across AWS, Azure, Google Cloud, and VMware. It operates a services-led business model with consulting and ongoing management for regulated and mission‑critical workloads, including healthcare. Founded in 1998 and headquartered in San Antonio, Texas, Rackspace is majority‑owned by Apollo Global Management.