Data Engineer II

🕒 il y a 8 jours

Postuler Maintenant

Trouver des Emplois à Distance Similaires

Configurer une alerte email pour les nouveaux emplois

📊 Vérifiez votre score de CV pour ce poste

Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

Télécharger le CV

mPulse

Site WebLinkedInTous les Emplois

501 - 1000 employés

🏥 Santé

☁️ SaaS

🤝 B2B

💰 Series unknown en 2022-02

Healthcare • SaaS • B2B

mPulse est une entreprise spécialisée dans les expériences et les informations en santé qui propose une plateforme d'Expérience et d'Informations en Santé (HXI) alimentée par l'IA, ainsi qu'une gamme de produits : analyses prédictives, communications de base, engagement omnicanal, portails de santé, gestion de contenu et acquisition & paiements, pour aider les régimes de santé, les systèmes de santé et autres organisations de santé à améliorer l'engagement des membres, combler les lacunes de soins et répondre aux exigences réglementaires. Leur plateforme offre des communications personnalisées et automatisées, basées sur des données, à grande échelle pour soutenir Medicare, Medicaid, les plans commerciaux, les TPAs, les ACOs, les pharmacies et les sciences de la vie/essais cliniques. mPulse met l'accent sur la modernisation des portails membres, les communications de gestion de l'utilisation, la performance CAHPS/HOS et le ciblage précis pour stimuler les résultats cliniques et financiers pour les clients (utilisés par plus de 400 organisations de santé selon leurs documents).

Description

• Design, develop, and maintain scalable data pipelines (ETL/ELT) to support ingestion, transformation, and delivery of high-volume healthcare data. • Write, optimize, and maintain complex SQL queries for data transformation, validation, and performance tuning. • Develop and manage workflow orchestration using Apache Airflow, including DAG creation, monitoring, and troubleshooting. • Enhance and scale data platform capabilities to support analytics, product features, and AI/ML use cases. • Build and maintain data quality frameworks, including automated data profiling, validation, and testing processes. • Monitor and optimize pipeline performance, reliability, and efficiency in production environments. • Analyze complex data issues, identify root causes, and implement scalable solutions, clearly communicating findings to both technical and non-technical stakeholders. • Collaborate with cross-functional teams (Data Operations, Product, Analytics, Data Science) to gather requirements and deliver high-quality data solutions. • Partner with clinical and analytics teams to operationalize data-driven insights and reporting solutions. • Contribute to documentation of data pipelines, data models, and engineering processes to support maintainability and knowledge sharing.

🎯 Exigences

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience. • 3+ years of professional experience in data engineering or a related field. • Strong proficiency in SQL, including complex querying, data transformation, and performance optimization. • Proficiency in Python for data processing, automation, and integration tasks. • Experience designing and building data pipelines (ETL/ELT) to support data ingestion, transformation, and delivery. • Hands-on experience with modern data warehousing platforms, such as Snowflake, PostgreSQL, Amazon Redshift, or Microsoft SQL Server. • Experience with workflow orchestration tools, particularly Apache Airflow (DAG development, debugging, and maintenance). • Experience using dbt (data build tool) to develop, test, and manage modular data transformation workflows. • Experience working with cloud platforms, particularly AWS (e.g., S3, RDS, Lambda, Glue, DMS). • Experience with version control systems and collaborative development workflows, such as GitHub or Bitbucket. • Familiarity with CI/CD practices and tools, such as Jenkins or GitHub Actions. • Experience supporting data quality initiatives, including data profiling, validation, or monitoring frameworks. • Familiarity with data modeling and data warehousing concepts, including dimensional modeling. • Exposure to analytics, reporting, or data visualization tools (e.g., Tableau, Looker) is a plus. • Experience working with healthcare data, including claims or clinical datasets, is a plus. • Familiarity with data science or machine learning workflows from a data engineering perspective is a plus.

🏖️ Avantages

• 100% Company-Paid Employee Coverage - Medical, dental, and vision plans with a 100% company-paid employee-only option, plus company contributions toward dependent coverage and company-paid life and disability insurance. • 401(k) + 4% Match • 6 Weeks Parental Leave • Invest in You - 30-60-90 day plans and frequent training • Culture of Recognition - peer-to-peer bonuses & team celebrations