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Principal Engineer - Data and Infrastructure, Remote

Aledade
Remote, USA
Full-time
Senior Level
Remote
Discovered 1 weeks ago
Free

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  • Architect complex systems and make critical technical decisions.
  • Solve challenging technical problems with innovative solutions.
  • Mentor engineers and promote engineering excellence across teams.
  • Align technical strategies with business goals through cross-functional collaboration.
  • Contribute to technical roadmaps and strategic planning.
  • Evaluate new technologies and lead innovation initiatives.
  • BS/BTech (or higher) in Computer Science, Engineering or a related field required
  • 10+ years of production-level experience as an engineer building highly scalable systems
  • 6+ years of experience acting as a trusted technical decision-maker in a team setting, solving for short-term and long-term business value
  • 4+ years of experience working with SQL or other database querying languages on large multi-table data sets
  • Experience architecting, developing, and deploying large-scale distributed systems at scale
  • Experience with cloud technologies, e.g., AWS, Azure, GCP
  • Experience building continuous integration and continuous development (CI/CD) pipelines
  • Strong familiarity with server-side web technologies (eg: Java, Python, Scala, C#, C++, Go)
  • 10+ years of production-level experience as an engineer building highly scalable and reliable infrastructure
  • Strong background in architecting or implementing AI-driven features - with the ability to translate AI capabilities into scalable and performant products
  • Proven track record in end-to-end architecture and delivery - guiding large teams (50+ engineers) across multiple product areas from initial conception through maturity.
  • Ability to lead and mentor senior engineering talent, shaping architecture decisions and technical direction across multiple teams
  • Demonstrated success evaluating and adopting emerging technologies to drive company-wide technical strategies
  • Experience working with data ingestion systems and optimizing performance for handling large-scale data processing and analysis
  • Deep hands-on expertise with cloud infrastructure (AWS preferred), event streaming (Kafka), data processing (Databricks and Kafka), and large-scale database systems
  • Familiarity with database replication, sharding and other techniques for scalability and high availability of databases
  • Experience engineering systems for scalability, high availability, and security — with a focus on sensitive or regulated data
  • Experience building observability platforms, performance monitoring, and optimization frameworks for large-scale systems and infrastructure.
  • Expertise in containerization/orchestration technologies (Docker, Kubernetes) and modern CI/CD pipelines
  • Experience with health-tech systems (like Electronic Health Records, Clinical data, etc.) is desired

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