Senior Data Engineer, Ingeniero de Datos Senior

November 14

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Cotiviti

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Healthcare Insurance • Fintech • Artificial Intelligence

Cotiviti is a healthcare technology and analytics company that specializes in improving payment accuracy and performance through advanced data analytics solutions. They partner with health plans, government agencies, and healthcare providers to deliver insights that enhance quality and efficiency in care delivery. With solutions such as risk adjustment, payment policy management, and member engagement, Cotiviti aims to optimize financial and clinical outcomes for the healthcare ecosystem.

5001 - 10000 employees

⚕️ Healthcare Insurance

💳 Fintech

🤖 Artificial Intelligence

📋 Description

• Design, build, and maintain efficient, scalable, and secure ETL pipelines to support data science and machine learning workloads • Optimize data flow and collection processes for both batch and real-time systems • Automate data ingestion, transformation, and integration workflows to support advanced analytics and ML pipelines • Monitor and troubleshoot pipeline issues to ensure reliability and scalability • Work with various databases, data warehouses, and cloud storage systems • Implement best practices in database architecture, performance tuning, security, and cost efficiency • Ensure the accuracy, consistency, and reliability of data across pipelines • Collaborate with team members to identify, document, and resolve data issues • Build and support pipelines for model retraining, performance tracking, and feature engineering • Mentor junior engineers and promote a culture of engineering excellence and peer learning

🎯 Requirements

• Bachelor’s degree in data engineering, big data, data analytics/science, computer science or other quantitative fields • Minimum of 5 years of relevant experience • Proven experience working with big data tools and platforms such as Spark, Hadoop, Oracle, or AWS S3 • Advanced proficiency in SQL, with experience in databases like SQL Server, MySQL, or Oracle • Strong understanding of data modeling for ML, including feature store management and serving strategies • Hands-on experience in building ETL pipelines, data warehousing solutions, and integrating analytic tools • Experience with MLOps tools such as MLflow, Airflow, or Kubeflow is a plus • Fully bilingual in English and Spanish (written and verbal)

🏖️ Benefits

• Competitive benefits package to address a wide range of personal and family needs.