Director, Data Engineering

🕒 il y a 1 jour

🐊 Florida, Montana, +3 états de plus – Distant

🐊 Florida – Remote 🦬 Montana – Remote 🍂 Massachusetts – Remote 🚗 Michigan – Remote ⚓ Rhode Island – Remote

💵 $195 000 - $210 000 / an

⏰ Temps Plein

🔴 Expert

🚰 Ingénieur Data

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AmeriLife

Site WebLinkedInTous les Emplois

1001 - 5000 employés

Fondée en 1973

🏥 Santé

💼 Conseil

💸 Finance

💰 Secondary Market en 2022-06

Healthcare • Consulting • Finance

AmeriLife est une organisation indépendante de premier plan spécialisée dans le marketing et un conseiller en investissements agréé aux États-Unis. Elle offre des solutions complètes en assurance et en finance aux agents, conseillers et consommateurs, avec pour objectif d'aider les personnes à vivre plus longtemps et en meilleure santé. AmeriLife collabore avec de nombreux assureurs, organisations de marketing financier (FMO) et experts du secteur pour fournir des solutions de santé et financières à des millions d'Américains chaque année. Avec un vaste réseau de plus de 300 000 agents et conseillers axés sur le client, AmeriLife propose des solutions technologiques avancées et des outils, comme l'Agent Xcelerator®, pour améliorer la qualité du service et la croissance des affaires. Leur engagement envers le leadership est évident à travers leur réseau de distribution étendu et des opportunités de partenariat innovantes.

Description

• Build, lead, and mentor a high-performing Data Engineering organization • Establish engineering standards, development practices, coding standards, and delivery frameworks • Foster ownership, innovation, automation, and continuous improvement • Develop future engineering leaders through coaching and mentorship • Serve as technical leader and subject matter expert for the Databricks Lakehouse Platform • Define enterprise Databricks standards and best practices • Lead adoption of Unity Catalog, Lakeflow, Delta Lake, AI/ML, Workflows, and performance optimization • Establish reusable engineering frameworks and partner with Databricks product teams and strategic partners • Lead migration of legacy ETL workloads to modern Databricks ELT architectures • Design scalable, resilient, cloud-native data pipelines • Drive automation across ingestion, transformation, orchestration, deployment, monitoring, and recovery • Optimize performance, scalability, reliability, and cloud cost management • Build reliable data pipelines supporting analytics, AI, operational reporting, and executive decision-making • Collaborate with Data Architecture on enterprise information models and integration patterns • Partner with Data Governance & Trust on governance, metadata, lineage, and quality • Enable reusable enterprise data products • Establish CI/CD, automated testing, infrastructure as code, and DevOps best practices • Improve observability, monitoring, and operational excellence • Lead root cause analysis and continuous improvement initiatives • Define engineering KPIs and improve delivery performance

🎯 Exigences

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field • 10+ years of enterprise Data Engineering experience • 5+ years leading Data Engineering teams within large enterprise environments • Expert-level experience designing and implementing enterprise solutions using the Databricks Lakehouse Platform • Deep expertise in Apache Spark, Delta Lake, SQL, Python, PySpark, and distributed data processing • Strong knowledge of Unity Catalog, Delta Live Tables (Lakeflow), Databricks Workflows, notebooks, cluster optimization, and platform administration • Proven experience modernizing enterprise data platforms and migrating legacy ETL solutions • Experience implementing CI/CD pipelines, Git-based development, Infrastructure as Code, and DevOps practices • Strong understanding of Medallion Architecture, dimensional modeling, and modern enterprise data architectures • Excellent communication, leadership, and stakeholder management skills • Master's degree preferred • Databricks Certified Data Engineer Professional certification preferred • Experience with Azure cloud services and enterprise security preferred • Experience with Data Vault 2.0 preferred • Knowledge of AI, machine learning, and enterprise analytics platforms preferred • Insurance or Financial Services industry experience preferred • Experience leading enterprise-scale modernization initiatives preferred • Employment offers are contingent upon successful completion of a background screening

🏖️ Avantages

• Discretionary annual bonus eligibility • PTO • Medical insurance • Dental insurance • Vision insurance • Retirement savings • Disability insurance • Life insurance