Senior Data Engineer

🕒 March 17

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Marisa.Care

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2022

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

Artificial Intelligence • SaaS • B2B

Marisa. Care is a Brazilian healthtech startup offering an AI-powered patient navigation and engagement platform for hospitals and clinics. Its platform analyzes patient data and real-time interactions (including WhatsApp) to identify risks, recommend exams and procedures, automate scheduling and follow-up, improve adherence and clinical outcomes, and generate qualified leads for cross-sell/upsell. It focuses on increasing hospital revenue, patient retention and operational efficiency while supporting preventive, integrated care.

📋 Description

• Design, build and maintain robust data pipelines (ETL/ELT) that feed both traditional ML models and production RAG and LLM systems; • Ensure data quality, governance and traceability using best practices for data contracts, cataloging, and versioning of datasets and artifacts; • Design and operate MLOps platforms — feature stores, model registry, experiment tracking, serving, and production performance monitoring; • Implement continuous retraining pipelines, drift detection, and objective criteria for model promotion and rollback based on business and technical metrics; • Integrate data and ML pipelines into CI/CD workflows, ensuring reproducibility and traceability of experiments; • Establish data observability: tracing, logs, quality metrics, and alerts for pipeline and model degradation; • Collaborate closely with the AI team to build RAG pipelines — ingestion, chunking, indexing, embeddings, and hybrid search; • Ensure compliance with LGPD and healthcare sector regulations, applying best practices for data masking, PII management, and security by design.

🎯 Requirements

• Proven experience as a Senior Data Engineer or in an equivalent role within high-scale digital products; • Proficiency in Python for data engineering and ML pipelines; • Experience with cloud platforms (Azure, AWS, or GCP) and pipeline orchestration tools (Airflow, Prefect, or equivalents); • Experience with MLOps platforms: MLflow, Databricks, SageMaker, or similar; • Strong knowledge of SQL, NoSQL, and vector databases, as well as messaging/event systems (Kafka, RabbitMQ, or equivalents); • Familiarity with production LLMs and RAG systems — or a strong willingness to learn; • Knowledge of data security, PII masking, and compliance with LGPD and healthcare regulations; • Ability to work autonomously, deliver high-quality results, and communicate technical decisions clearly to both technical and non-technical audiences.