Data Engineering Manager

🕒 Agosto 24

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $180.000 - $208.000 / ano

⏰ Tempo Integral

🟡 Pleno

🟠 Sênior

👮‍♀️ Gerente de Engenharia de Software

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OpenSesame

SiteLinkedInTodas as Vagas

51 - 200 funcionários

Fundada em 2011

💼 Consultoria

🏥 Saúde

📣 Marketing

Consulting • Healthcare • Marketing

A OpenSesame é uma empresa especializada em fornecer soluções abrangentes de treinamento online para negócios em diversos setores. Ela oferece um mercado robusto de cursos que atendem a várias necessidades de treinamento, como conformidade, liderança, gestão, diversidade, equidade, inclusão, bem-estar e tecnologia. A OpenSesame foca em integrar-se perfeitamente com as pilhas de tecnologia existentes e fornece ferramentas e orientação especializada para ajudar as empresas a criar trajetórias de desenvolvimento de habilidades adaptadas aos seus objetivos específicos. Desde 2011, a OpenSesame tem se dedicado a desbloquear o potencial dos funcionários ao redor do mundo, fechando lacunas críticas de habilidades e aprimorando programas de treinamento no local de trabalho.

Descrição

• Guide and grow a lean data engineering team • Build and scale an AI-ready data foundation for analytics, operational reporting, governance, enterprise integrations, and AI initiatives • Own the Data Governance & Accessibility program • Serve as managerial and architectural lead for scalable data systems and reliable pipelines • Conduct 1:1s, set goals, provide performance feedback, and manage career growth • Mentor engineers in data engineering best practices, design patterns, testing, and operational discipline • Drive execution, manage team velocity, remove bottlenecks, and maintain operational sustainability • Facilitate planning, standups, prioritization, and retrospectives • Partner with analysts and business leaders to translate needs into incremental stories • Act as primary technical contact for analytics and business leaders • Communicate roadmaps, risks, delays, and progress transparently • Translate technical concepts into business terms • Direct Snowflake platform, ingestion architecture, and AI interface layer design and scaling • Oversee data ingestion from enterprise systems into a centralized source of truth • Establish data governance and observability standards • Audit the data ecosystem and evaluate cloud spend, reliability, transformations, data quality, and AI readiness • Define engineering standards and implement pipeline reliability improvements • Draft and deliver modernized data architecture recommendations • Establish self-service analytics governance • Execute the initial phase of the approved architecture and deliver production-ready pipelines and documented datasets • Build a high-performing engineering culture and position data engineering as a strategic enabler for AI and data initiatives

🎯 Requisitos

• Proven examples of building brands, creating scalable systems, and driving measurable marketing impact • Ability to conduct people management, including 1:1s, performance management, and career development • Experience with data engineering best practices, design patterns, testing strategies, and operational discipline • Ability to facilitate agile planning, standups, retrospectives, and prioritization • Ability to translate business needs into well-defined, incremental stories • Experience designing and scaling Snowflake-based data platforms, ingestion architecture, and AI interface layers • Experience overseeing integrations with Salesforce, HubSpot, NetSuite, Zendesk, Jira, and Confluence • Knowledge of data ownership, access management, lineage visibility, testing/validation, and automated pipeline monitoring • Experience with Snowflake, Fivetran, dbt, and Looker • Ability to work remotely from anywhere in the United States

🏖️ Benefícios

• Professional development • Incentive stock options (ISOs) • Comprehensive medical coverage • Dental coverage • Vision coverage • Flexible PTO • 401(k) matching • Volunteer time off • Employee Resource Groups • Generous professional development program with dedicated annual time off for learning and growth • Hands-on AI training with clear guardrails for responsible experimentation • Remote-first work arrangement • All-company in-person meetings several times a year • Up to 15 days of travel per year; senior management and leadership teams require up to 35 days

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