Senior Data Engineer, Data and Applied AI

Emploi pas sur LinkedIn

🕒 il y a 3 mois

🇺🇸 États-Unis – Télétravail

💵 €158 000 - €168 000 / an

⏰ Temps Plein

🟠 Senior

🚰 Ingénieur Data

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Plume

Site WebLinkedInTous les Emplois

51 - 200 employés

Fondée en 2020

🏥 Santé

⚕️ Assurance santé

🧘 Bien-être

Healthcare • Healthcare Insurance • Wellness

Plume est une clinique virtuelle de soins affirmant le genre, exclusivement destinée aux personnes trans et non conformes au genre. L'entreprise propose une thérapie hormonale complète affirmant le genre et des services de bien-être, accessibles via un modèle de télémédecine qui élimine les barrières traditionnelles aux soins. Plume se concentre sur la fourniture de soins de santé centrés sur les trans, le soutien et l'engagement communautaire, offrant des services tels que l'accompagnement de transition, le soutien contre l'anxiété et la dépression, le traitement de l'acné, l'arrêt du tabac, et bien plus encore. Avec des services disponibles dans 47 états, Plume s'engage à soutenir la communauté trans dans leur parcours de genre avec des soins pratiques et affirmants.

Description

• Building and maintaining production-grade data pipelines in cloud data warehouses such as Google BigQuery or equivalent, following architectural standards set by the Director of Data and AI. • Designing and developing dbt models across bronze, silver, and gold layers, including a focus on quality and governance via automated tests, documentation, and incremental load strategies. • Creating and optimizing Airflow DAGs for data workflow orchestration, including scheduling, dependency management, error handling, and alerting. • Implement dimensional data models and data mart structures — guided by the team's modeling standards — that support clinical BI and ML feature consumption. • Crafting easy-to-understand visualizations and dashboards that align with commonly used business analytic standards in Looker or equivalent BI tools in close collaboration with product analytics, finance, operations, growth, and clinical stakeholders. • Integrating healthcare data from sources such as EHRs, Stripe, 3rd-party APIs, and application database feeds, normalizing incoming data into the unified data platform. • Applying HIPAA-compliant data handling practices, including PHI/PII masking, tokenization, audit logging, and role-based access controls across all pipeline and AI system work. • Architecting and implementing RAG pipelines — including document ingestion, chunking, embedding generation, and retrieval — using frameworks such as LangChain or LangGraph • Supporting MLOps workflows, including model training pipeline maintenance, deployment support, performance monitoring, and retraining triggers. • Code reviewing PRs from teammates, providing constructive technical feedback to peers, and upholding the team's engineering standards. • Collaborating closely with product managers to understand requirements and deliver reliable data and AI products. • Monitoring and triaging assigned pipeline and data quality failures, escalating architectural issues as appropriate. • Documenting pipeline designs, data models, and technical decisions in alignment with the team's governance and lineage tracking standards. • Evaluating new tools and frameworks, providing hands-on prototyping and technical assessments.

🎯 Exigences

• 5+ years of hands-on experience in data engineering, analytics engineering, or a closely related role. • 2+ years of experience working within the healthcare industry, including working knowledge of healthcare data standards, clinical workflows, regulated data environments, and domain-specific data visualizations. • Working knowledge of HIPAA — including PHI/PII classification, data masking, audit logging, and access control requirements. • Proven production experience with at least one major cloud data warehouse: BigQuery, Snowflake, or Redshift — including advanced SQL and query optimization. • Strong hands-on experience with dbt (Core or Cloud), including incremental models, tests, documentation, and multi-environment workflows. • Deep experience with Apache Airflow for workflow orchestration, including DAG design, scheduling, monitoring, and failure handling. • Demonstrated knowledge of dimensional data modeling — star/snowflake schemas, SCD Types 1/2, fact and dimension table design. • Hands-on experience delivering dashboards and reports in at least one enterprise BI tool: Looker, Power BI, Tableau, Qlik, etc. • Proficiency in Python for data pipeline development, API integrations, and automation (Pandas, PySpark, or similar). • Practical exposure to RAG pipeline development and LLM integration using LangChain, LangGraph, or LlamaIndex • Hands-on exposure to MLOps concepts — model deployment, monitoring, and retraining workflows • Knowledge of CI/CD tooling for data and AI workloads (GitHub Actions, dbt Cloud CI) • Strong understanding of data quality and governance principles: lineage, access controls, data contracts, and automated testing and experience with data governance tools such as OpenMetadata • Excellent written and verbal communication skills with the ability to collaborate effectively across engineering, analytics, and clinical teams • Ability to work independently on assigned workstreams while keeping the Director and team informed of progress, blockers, and risks

🏖️ Avantages

• Ground-Floor Equity (Series B) • Free Medical, Dental, and Vision on the first of the month after you start full-time work • Unlimited PTO • 11 paid holidays and company shut-down for a week in December • 401(k) • Free Plume and BetterHelp Subscriptions