Senior Data Engineer

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🕒 Junho 3

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Ceresti Health

SiteLinkedInTodas as Vagas

11 - 50 funcionários

Fundada em 2013

⚕️ Seguro de Saúde

🤝 B2B

🔥 Investimento no último ano

💰 $11.726.799 Venture Round - Ceresti Health em 2025-08

Healthcare Insurance • B2B

A Ceresti Health é uma empresa de assistência habilitada por tecnologia que faz parceria com planos de saúde e organizações de cuidados responsáveis (ACOs) para apoiar cuidadores familiares de pessoas com demência. A empresa combina a estratificação de risco orientada por dados de sinistros, educação para cuidadores, uma plataforma baseada em tablet e navegadores de cuidados pessoais semanais para melhorar a adesão ao plano de cuidados, fechar lacunas nos determinantes sociais de saúde e detectar proativamente mudanças nas condições dos pacientes. O programa liderado por cuidadores da Ceresti possui resultados validados de forma independente que mostram reduções substanciais em hospitalizações evitáveis e nos custos médicos por paciente, oferecendo contratos baseados em resultados sem risco para pagadores.

Descrição

• Design and own Ceresti’s end-to-end data architecture: a landing zone with secure cloud object storage for raw partner files and API payloads, validated ingestion pipelines into our transactional Postgres, and a curated analytics layer that decouples reporting and AI workloads from production • Build ingestion pipelines for the data we receive today, including partner data files (CSV/JSON/XML/HL7/X12 as applicable) and REST/SFTP API integrations with schema validation, quarantine of bad records, and full lineage from raw bytes to curated row • Stand up and operate the curated layer (data warehouse / lakehouse-lite) so analytics and ML models can consume data without slowing down the transactional system • Choose, integrate, and operate the smallest set of tools needed, including object storage, an orchestrator (Dagster, Prefect, Airflow, etc.), dbt or similar for transformations, a single validation library (Great Expectations / Pandera / Soda) • Design and enforce data governance for a HIPAA-regulated environment: PHI/PII classification, encryption in transit and at rest, role-based access, audit logging, retention and minimum-necessary policies, and de-identification where appropriate • Partner with backend, ML, product, and clinical stakeholders to define data contracts with our health plan and ACO partners and hold the line on data quality • Build and maintain reliable feature data for ML models, including embeddings (e.g., pgvector) and curated feature tables for risk stratification, engagement, and outcomes work • Instrument the data platform for observability including pipeline SLAs, data freshness, schema drift, quality metrics, and act on what the data tells you • Participate fully in our Agile process: backlog grooming, sprint planning, demos, and retrospectives • Mentor engineers across the team on SQL, schema design, and the craft of building data systems that are boring in the best possible way

🎯 Requisitos

• BS/BA degree or higher in Computer Science, Engineering, or a related technical field • 8+ years of professional data engineering experience, with a track record of shipping production data systems end-to-end • Mastery of PostgreSQL: schema design, indexing, query tuning, partitioning, logical replication, JSONB, extensions (pg_partman, pg_cron, pgvector, etc.), and operating Postgres at scale • Strong experience designing and operating data pipelines, including file-based ingestion (SFTP / object storage drops) and API-based ingestion (REST, webhooks) • Hands-on experience with one or more cloud platforms (AWS preferred) and their data primitives: object storage (S3), managed Postgres • Experience designing data warehouses and/or data lakes and the judgment to know which one a given problem actually needs • Strong experience with dbt (or equivalent SQL-based transformation framework) and modern data modeling patterns (Kimball dimensional, Data Vault, One Big Table — and an opinion about when each is right) • Experience with at least one orchestration framework (Dagster, Prefect, or Airflow) and a clear point of view on which to use when • Strong Python skills for ingestion, validation, and tooling • Experience with data validation and data-quality frameworks (Great Expectations, Pandera, Soda, or equivalent) • Experience with change-data-capture from Postgres (logical replication, or equivalent) • Data governance experience in a HIPAA-regulated environment or, at minimum, demonstrated instincts for protecting PHI and PII (encryption, least privilege, audit, de-identification, BAA-aware vendor selection); HITRUST or SOC 2 experience is a strong plus • Comfortable with infrastructure-as-code and CI/CD for data systems • Experience supporting ML workloads: building feature tables, managing training data, serving features at inference time; familiarity with embeddings, vector search (pgvector or equivalent), and LLM integration patterns (RAG, prompt-grounded analytics) is a plus • Excellent written and verbal communication skills: you can explain a tricky schema decision to a business stakeholder and a data contract to a partner with equal clarity • Demonstrated experience working in Agile/Scrum teams

🏖️ Benefícios

• Competitive salary and benefits package • Opportunities for professional growth and development • Collaborative and dynamic work environment • Flexible work arrangements and remote work options • Access to cutting-edge technologies and tools