Data Engineering Manager

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $180k - $208k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

👮‍♀️ Software Engineering Manager

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OpenSesame

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2011

💼 Consulting

🏥 Healthcare

📣 Marketing

Consulting • Healthcare • Marketing

OpenSesame is a company that specializes in providing comprehensive online training solutions for businesses across various industries. It offers a robust marketplace of courses that cater to numerous training needs such as compliance, leadership, management, diversity, equity, inclusion, wellness, and technology. OpenSesame focuses on integrating seamlessly with existing tech stacks and provides tools and expert guidance to help businesses craft skill-building paths tailored to their specific goals. Since 2011, OpenSesame has been dedicated to unlocking the potential of employees around the globe by closing critical skill gaps and enhancing workplace training programs.

📋 Description

• 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

🎯 Requirements

• 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

🏖️ Benefits

• 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