Data Engineer

Emploi pas sur LinkedIn

🕒 il y a 22 jours

🇺🇸 États-Unis – Télétravail

⏰ Temps Plein

🟢 Junior

🟡 Intermédiaire

🚰 Ingénieur Data

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Vytalize Health

Site WebLinkedInTous les Emplois

201 - 500 employés

🏥 Santé

☁️ SaaS

⚕️ Assurance santé

💰 €100 000 000 Series C - Vytalize Health en 2023-02

Healthcare • SaaS • Healthcare Insurance

Vytalize Health est une entreprise de technologie et de services de santé qui aide les cabinets de soins primaires et les Organisations de Soins Responsables (ACOs) à passer à des soins basés sur la valeur. Elle combine des analyses basées sur les données, un soutien clinique virtuel et à domicile, et des services de gestion des soins pour améliorer les résultats pour les patients, permettre des services à distance approuvés par Medicare pour les maladies chroniques, et aider les cabinets à réaliser des économies partagées dans le cadre de contrats basés sur la valeur. Vytalize s'associe à des médecins généralistes indépendants, à des groupements de praticiens, à des centres de santé communautaires et à des ACO existants pour offrir une capacité clinique, des flux de travail adaptés aux pratiques, et des informations sur la performance.

Description

• Handle support tickets and operational issues reported by internal teams and external partners; investigate root causes and coordinate resolution with senior engineers • Perform KTLO (Keep The Lights On) tasks including monitoring pipeline health, responding to alerts, validating data quality, and investigating data anomalies • Conduct data source discovery and profiling work — examining raw data sources, documenting data structure, identifying quality issues, and recommending integration approaches • Assist with data validation and testing — writing SQL queries to validate data transformations, identifying gaps and inconsistencies, and flagging issues for review • Support data quality initiatives by running diagnostics, documenting data quality findings, and escalating issues with clear context for senior engineers • Assist in establishing and monitoring data quality metrics — working with senior engineers to define quality KPIs and track pipeline health • Help maintain and improve documentation for existing data systems, pipelines, and data sources — documenting schemas, transformation logic, and known issues • Assist senior engineers with debugging data pipeline issues — tracing data through transformations, validating intermediate outputs, and comparing expected vs. actual results • Conduct quality assurance activities — reviewing data outputs, testing transformations, and validating correctness before data reaches downstream consumers • Perform exploratory data analysis to understand data patterns, support analytics requests, and help answer business questions about data availability and quality • Learn and apply data engineering best practices including version control (Git), code review processes, and testing frameworks under guidance from senior engineers • Support infrastructure and operational tasks as assigned — assisting with deployments, maintaining environments, and supporting on-call activities • Participate in knowledge-sharing and mentorship; ask questions, document learnings, and contribute to team documentation and runbooks

🎯 Exigences

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent hands-on experience • Strong SQL proficiency — ability to write queries to explore, validate, and analyze data • Proficiency in Python or another programming language; comfort writing scripts and automation • Basic understanding of data modeling, ETL/ELT concepts, and data pipeline architecture • Familiarity with version control (Git) and collaborative development practices • Strong communication skills; ability to document findings clearly and ask clarifying questions • Analytical mindset and strong problem-solving skills, especially for data quality and debugging tasks • Attention to detail and commitment to data accuracy and reliability • Basic understanding of data quality concepts and the importance of testing and validation • Willingness to learn from experienced engineers and grow into a full data engineer role

🏖️ Avantages

• Health insurance • Professional development opportunities