Data Reliability Engineer

🕒 Julho 15

🇺🇸 Estados Unidos – Remoto (EUA)

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

⛑ DevOps & Engenheiro de Confiabilidade do Site (SRE)

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Vytalize Health

SiteLinkedInTodas as Vagas

201 - 500 funcionários

🏥 Saúde

☁️ SaaS

⚕️ Seguro de Saúde

💰 $100.000.000 Series C - Vytalize Health em 2023-02

Healthcare • SaaS • Healthcare Insurance

A Vytalize Health é uma empresa de tecnologia e serviços de saúde que auxilia consultórios de atenção primária e Organizações de Cuidados Responsáveis (ACOs) na transição para o cuidado baseado em valor. Ela combina análises orientadas por dados, suporte clínico virtual e domiciliar, além de serviços de gestão de cuidados para melhorar os resultados dos pacientes, viabilizar serviços remotos aprovados pelo Medicare para condições crônicas e ajudar práticas a obter economias compartilhadas em contratos baseados em valor. A Vytalize faz parcerias com médicos independentes, consultórios em grupo, centros de saúde comunitários e ACOs existentes para fornecer capacitação clínica, fluxos de trabalho adaptados às práticas e insights de desempenho.

Descrição

• Own and continuously improve the reliability of data pipelines across ingestion, transformation, and delivery layers, ensuring data is accurate, complete, and delivered on schedule. • Establish and maintain data reliability standards, including Service Level Indicators (SLIs), Service Level Objectives (SLOs), and Service Level Agreements (SLAs) for both upstream ingestion and downstream data delivery. • Design, implement, and maintain comprehensive monitoring, logging, and observability frameworks for data pipelines, datasets, and data services with clear visibility into freshness, volume, schema changes, and data quality. • Design and implement data quality testing and validation frameworks — establishing test cases, golden datasets, and regression tests to detect quality issues early. • Lead incident response for data reliability issues, including detection, triage, communication, root cause analysis, and post-incident remediation with documented corrective actions. • Drive improvements in pipeline resiliency through retry strategies, backfills, idempotency, schema enforcement, and safe deployment practices.

🎯 Requisitos

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field, or equivalent professional experience. • 5+ years of experience working with data platforms, data pipelines, or distributed data systems in production environments. • Demonstrated experience improving reliability, observability, or operational quality of data systems with measurable SLI/SLO/SLA improvements. • Hands-on experience supporting both data ingestion pipelines and downstream data consumption or delivery patterns. • 1+ years of hands-on experience with machine learning-based monitoring, anomaly detection, or AI-assisted observability tools. • Demonstrated experience with data quality testing, validation frameworks, and quality metrics definition. • Proficiency in Python and SQL, with experience building or supporting production-grade data pipelines. • Strong understanding of modern data architectures, including data lakehouse patterns and multi-layer (bronze/silver/gold) data models. • Experience with cloud-based data platforms (AWS, Databricks, or similar).

🏖️ Benefícios

• Health insurance • 401(k) matching • Flexible work arrangements • Professional development opportunities