Data Engineer

The application window is expected to close on: 07/30/2026.

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

Our team designs and oversees the deployment of technology architecture to capture and utilize structured and unstructured data from diverse sources. We build the essential structures that channel data through cloud and local databases to meet critical business and technical requirements. By leveraging artificial intelligence and machine learning, we automate the cleansing and organization of big data to ensure its integrity.

You will work in a collaborative environment, partnering with data scientists and business leaders to translate complex data into actionable insights. This role is vital to our organization, as we establish the design standards and assurance processes that ensure the compatibility of all data flows.

Lead moderately complex data projects from end-to-end, driving analyses from initial technical design through to successful completion. Develop and scale high-volume data pipelines and architectures to store, process, and visualize large datasets. Improve feature engineering and build innovative models to solve a variety of complex business problems. Optimize the reliability and velocity of deliverables by conducting thorough code reviews and writing clean, functional code.

Ensure data quality and compliance by monitoring pipeline performance and resolving multidimensional security or privacy flags.

• Bachelor’s degree with 7+ years of related experience, or a Master’s degree with 4+ years, or a PhD with 1+ year.
• Experience building and managing data pipelines from multiple internal and external sources.
• Proficiency in scripting languages and relational database management.
• Experience with cloud services and distributed data structures.
• Experience using big-data techniques to cleanse, organize, and transform data.

• Experience guiding others on database/data lake sources and security requirements.
• Ability to design and create reporting and visualizations that link data insights to business outcomes.
• Knowledge of threat modeling for data features and applications.
• Strong collaborative skills for partnering with data scientists and business stakeholders.
• Ability to identify risks and elevate complex technical issues within a project lifecycle.