Lead Data Engineer

About the role

We love going to work and think you should too. Our team is dedicated to trust, customer obsession, agility, and striving to be better everyday. These values serve as the foundation of our culture, guiding our actions and driving us towards excellence. We foster a culture of performance and recognition, allowing us to transform growth as we enable our employees to do the best work of their careers. This role is open to candidates based in or near Austin, TX. Our Austin office is based in the vibrant San Jacinto Center downtown with breathtaking views of Lady Bird Lake. At LogicMonitor, we hire within our Centers of Energy-vibrant locations where our teams connect, collaborate, and innovate. To learn more about life at LogicMonitor, check out our Careers Page .

Responsibilities

• Here's a closer look at this key role:
• Define and drive the architecture of scalable, reliable data pipelines that power analytics and data products across the organization
• Establish and enforce engineering standards to optimize pipelines, frameworks, and data systems for performance, cost efficiency, and developer velocity
• Lead the design of data models and transformation layers that convert raw, disparate data into trusted, high-quality, and reusable datasets
• Own complex data integration challenges, setting patterns and best practices to ensure consistency, scalability, and resilience across systems
• Architect and evolve the organization's data compute and storage platforms, balancing performance, scalability, and cost at enterprise scale
• Set strategy and governance for data security, privacy, and compliance, partnering with security teams to proactively mitigate risk
• Define and maintain enterprise data architecture standards, documentation, and reference models to guide long-term platform evolution
• Strategic Leadership
• Own the long-term strategy and roadmap for the data technology stack (e.g., Snowflake, dbt), aligning platform capabilities with business and product objectives
• Identify systemic gaps across infrastructure, tooling, and team processes; drive cross-functional initiatives to resolve root causes and improve engineering effectiveness
• Translate business priorities into scalable data platform capabilities, shaping and enabling high-impact data products and workflows
• Serve as the senior technical point of contact for data platform vendors, influencing roadmaps, driving feature adoption, and reducing friction for internal stakeholders

Requirements

• 6+ years extensive experience designing and scaling data platforms, pipelines, and models in distributed environments
• Expert in SQL and Python, driving engineering standards, performance optimization, and best practices
• Proven ownership of modern data stack architecture (e.g., Airflow, Snowflake, dbt), including orchestration, transformation, and governance
• Strong expertise in cloud-based data systems with a focus on scalability, reliability, and cost efficiency
• Experience enabling AI/ML use cases and building data foundations for advanced analytics
• Residents of California, cl

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