Staff Data Engineer

🕒 il y a 1 mois

🌲 North Carolina – Distant

🌲 North Carolina – Remote

💵 $216 000 / an

⏰ Temps Plein

🔴 Expert

🚰 Ingénieur Data

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Teamworks

Site WebLinkedInTous les Emplois

501 - 1000 employés

Fondée en 2005

💼 Conseil

🏥 Santé

📦 Logistique

💰 €235 000 000 Series F - Teamworks en 2025-06

Consulting • Healthcare • Logistics

Teamworks est un "Système d'Exploitation" SaaS pour le sport qui unifie la communication, la gestion des effectifs et du personnel, la planification, la performance, l'entraînement, la conformité, l'inventaire, la nutrition et d'autres opérations pour les équipes professionnelles, universitaires, olympiques/NGB et militaires/tactiques. La plateforme centralise les flux de travail, le partage de fichiers, les processus automatisés et l'analyse basée sur l'IA (Teamworks Intelligence) pour informer l'acquisition de talents, la construction des effectifs, l'évaluation des athlètes et la stratégie de jeu. Teamworks sert des milliers d'équipes et des centaines de départements universitaires et d'organisations professionnelles dans le monde entier, aidant les organisations à coordonner le personnel et les athlètes, à rationaliser les opérations et à améliorer la performance.

Description

• Define the technical architecture and platform standards for our lakehouse on AWS: distributed cloud architecture, schema conventions, multi-tenant isolation, and integration design • Lead design and delivery of the production pipelines that consolidate performance and product data, and own data modeling for complex entities (time-series, hierarchical, multi-source) so the models serve products, analytics, and ML • Introduce just enough data governance, ownership, and stewardship to raise our data maturity, and lay the catalog and semantic-layer foundation that analytics, ML, and AI agents can reason over • Author and maintain the Data Platform playbook (reusable patterns, ADRs, runbooks, Terraform modules) with data quality and reliability built in, so product teams can self-serve new datasets and integrations • Lead delivery end to end, from requirements and planning through coordinating workstreams and translating status to senior leadership and non-technical partners • Mentor engineers across levels, raise the bar through design review and on-call ownership, and be the engineering voice shaping the platform roadmap

🎯 Exigences

• 10+ years of data engineering or related experience, with strong Python for pipelines, transformations, and platform tooling • Deep expertise designing, operating, and setting direction for lakehouse platforms (Delta Lake, Iceberg, or Hudi) and modern processing engines (Spark, Databricks, Trino, or Snowflake) at production scale, with the judgment to make the hard tradeoffs and troubleshoot them • Expert AWS and distributed cloud architecture experience (S3, IAM, Glue, EMR/Lambda, networking), fluent writing Terraform and the best practices for implementing those designs • Deep data modeling and schema design for complex entities (time-series, hierarchical, multi-source) in multi-tenant environments, across multiple systems you've built (warehouses, lakehouses, relational), plus proven integration standards across teams (event-driven, API, batch) • Track record of standing up or significantly maturing a data platform from ambiguous goals, including the organizational work of aligning leaders and teams and communicating decisions to senior and non-technical stakeholders through RFCs and ADRs • Familiarity with how data governance, ownership, and stewardship programs are introduced, and the judgment to apply just enough to raise data maturity without over-engineering it

🏖️ Avantages

• Offers Equity • Offers Bonus