Staff Software Engineer, Data Products

🕒 il y a 17 jours

🇺🇸 États-Unis – Télétravail

💵 $202 400 - $253 000 / an

⏰ Temps Plein

🔴 Expert

🚰 Ingénieur Data

🦅 Parrain de Visa H1B

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Omada Health

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 2011

🏥 Santé

⚕️ Assurance santé

🧘 Bien-être

💰 €192 000 000 Series E en 2022-02

Healthcare • Healthcare Insurance • Wellness

Omada Health est une entreprise de soins virtuels axée sur l'aide aux individus pour atteindre leurs objectifs de santé grâce à un accompagnement personnalisé et à des programmes sur mesure. La société offre des solutions complètes de gestion de la santé pour des conditions comme le diabète, l'hypertension et la santé musculo-squelettique. Omada propose un coaching santé individuel et des dispositifs intelligents pour surveiller et améliorer la santé, créant ainsi des plans de soins personnalisés pour ses utilisateurs. Ses programmes sont conçus pour être accessibles sans frais pour les participants lorsqu'ils sont couverts par leur employeur ou leur assurance santé, faisant d'Omada un leader dans la fourniture de soins virtuels de qualité, tant personnels que durables.

Description

• Design, build, and maintain reusable feature datasets that support machine learning use cases including personalization, engagement, risk prediction, churn modeling, recommendation systems, and experimentation. • Establish self-service foundations that streamline and democratize dataset creation across the data organization. • Partner with Data Scientists to translate modeling requirements into production-ready feature pipelines, supporting the full model lifecycle from exploration to deployment. • Identify source data, transformations, and historical windows needed for feature engineering. Help define and build shared, reusable feature definitions across models rather than one-off datasets. • Balance features freshness, correctness, latency, and computational efficiency when designing data pipelines. • Build datasets that support both historical model training and future production inference. • Design and implement batch and streaming pipelines that transform raw healthcare, behavioral, product, and operational data into trusted ML-ready datasets. • Build reliable data processing systems using Python, SQL, Spark, and modern cloud data platforms. • Optimize large-scale distributed processing for performance, scalability, and cost. • Design data pipelines that are modular, testable, observable, and easy to evolve as product requirements change. • Ensure data quality through testing, anomaly detection, schema validation, and pipeline monitoring. • Partner with platform teams to support near real-time feature generation where appropriate. • Improve reproducibility by standardizing feature computation across experimentation and production. • Support rapid experimentation without sacrificing long-term maintainability. • Establish engineering standards for correctness, documentation, and maintainability. • Familiarity with feature stores or feature management platforms. • Familiarity with model training pipelines and MLOps workflows.

🎯 Exigences

• 8+ years building large-scale production data platforms and distributed data pipelines. • Experience designing reusable datasets that power machine learning, experimentation, or advanced analytics. • Demonstrated experience partnering closely with Data Scientists to productionize feature engineering workflows. • Experience leading cross-team technical initiatives and influencing engineering direction. • Strong experience working with cloud-native data platforms such as AWS. • Experience building production data systems using Databricks, Iceberg, Spark, Redshift, Snowflake, or similar technologies. • Experience developing reliable batch and streaming data pipelines. • Experience working with healthcare, behavioral, or other large-scale event data is a plus.

🏖️ Avantages

• Competitive salary with generous annual cash bonus • Equity grants • Remote first work from home culture • Flexible Time Off to help you rest, recharge, and connect with loved ones • Generous parental leave • Health, dental, and vision insurance (and above market employer contributions) • 401k retirement savings plan • Lifestyle Spending Account (LSA) • Mental Health Support Solutions • ...and more!