Senior Manager – Data Engineering

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Magna Legal Services

Site WebLinkedInTous les Emplois

501 - 1000 employés

Fondée en 2007

💼 Conseil

🛡️ Assurance

📦 Logistique

💰 Debt financing en 2020-02

Consulting • Insurance • Logistics

Magna Legal Services est un fournisseur américain de services complets de soutien en matière de contentieux pour les cabinets d'avocats, les compagnies d'assurance, les entreprises et les agences gouvernementales. L'entreprise propose des services de sténographie judiciaire et de dépositions virtuelles, de récupération de dossiers, de signification judiciaire, de services d'enquête et de langue, de surveillance des réseaux sociaux, de recherche et de conseil auprès des jurés (JuryConfirm, JuryEvaluator, JuryScout), de présentation de procès et de graphiques, ainsi que tout support connexe au procès. Magna organise également des conférences juridiques et des programmes de formation continue (CLE/CE), et fournit des outils de planification nationale et en ligne pour soutenir les litiges, de la découverte au procès.

Description

• Serve as the internal authority on Snowflake architecture, performance tuning, cost governance, and security (RBAC, data masking, network policies). • Design and maintain a scalable, well-documented warehouse structure including database, schema, and object hierarchy standards. • Drive Snowflake feature adoption — dynamic tables, Snowpark, data sharing, and emerging capabilities. • Own the dbt project end-to-end: modeling conventions, testing strategy, documentation standards, and CI/CD integration. • Establish and enforce a layered modeling approach (staging → intermediate → marts) that downstream teams can trust and self-serve. • Lead the design and operation of data pipelines on Azure, including Azure Data Factory • Ensure reliable, monitored data movement from source systems into Snowflake with clear SLAs and alerting. • Manage, mentor, and grow a team of data engineers — running regular 1:1s, setting performance goals, and building a culture of engineering excellence. • Own hiring, onboarding, and career development for the data engineering function. • Translate business requirements from stakeholders into well-scoped, prioritized engineering work. • Define and enforce organization-wide ETL/ELT best practices, naming conventions, and code review standards. • Champion data quality, observability (e.g., dbt tests), and lineage across the platform. • Proactively identify opportunities for data process improvements and lead initiatives to implement these changes.

🎯 Exigences

• Bachelor’s degree in computer science, Information Technology, Engineering, or a related field • 7+ years in data engineering, with at least 2 years in a team lead or management role • Deep, production-grade Snowflake expertise — you have designed warehouse architectures, optimized query performance, managed costs, and implemented enterprise security controls • Fluency with dbt: you have built and maintained dbt projects at scale and can articulate opinionated best practices • Hands-on Azure Data Factory experience • Strong SQL skills and proficiency in Python for data pipeline development and automation • Proven ability to lead and grow a small team while remaining technically engaged • Strong communicator who can translate complex data concepts to non-technical stakeholders and contribute to strategic planning conversations