Data Engineering Manager

Husch Blackwell LLP is a full-service litigation and business law firm with multiple locations across the United States, serving clients with domestic and international operations.

At Husch Blackwell we believe that diverse, equitable and inclusive teams lead to better outcomes. Husch Blackwell is committed to retaining, recruiting, developing, and promoting talented lawyers and business professionals with diverse backgrounds and experiences. We foster an engaged, diverse, and inclusive team culture of accountability and purpose that makes our Firm and our communities better.

Our firm is committed to attracting and retaining professionals who value each other and the service we provide by embracing Teamwork, Collaboration, Client Service, and Innovation. If you are a motivated professional looking for a long-term fit where you can grow in a role, and will be valued and empowered, then we invite you to apply to our Data Engineering Manager position.

This position may be filled remotely or in a hybrid capacity in any of our Central and Eastern Time locations. Strong candidates located in Mountain Time will also be considered.

The Data Science & AI and Information Design & Engineering teams at Husch Blackwell build systems that transform data into actionable insights for better legal work. Projects are collaborative and fast-paced.

The Data Engineering Manager will lead the design and build-out of the firm’s cloud-based data platform from the ground up, establishing the foundational infrastructure needed to ensure high-quality data is available for analytics, reporting, applications, and AI. They will architect core systems to collect, consolidate, and organize data efficiently, making it accessible and well-documented for downstream teams to use in various tools and workflows.

Working with multiple stakeholders, they ensure the platform supports current and future needs, set standards for data engineering methods and product reliability, and coordinate teams to deliver trustworthy and secure data products.

They uphold standards for quality, lineage, documentation, and access control, contribute to data and AI governance, and integrate privacy and security requirements into data processes. The manager focuses on building user-friendly systems, simplifying complex landscapes, fostering experimentation, and communicating effectively with both technical and non-technical audiences. Essential functions include:

• Supervising all Data Engineering staff persons.
• Foster professional growth and skill development in their direct reports.
• Delegate tasks and responsibilities effectively, ensuring optimal workload distribution and project efficiency.
• Conduct regular performance evaluations, provide constructive feedback, and set clear goals for direct reports.
• Promote team engagement through regular communication, recognition, and a collaborative, inclusive environment.
• Identify training and development opportunities to keep team capabilities current with modern data engineering practices and cloud technologies.
• Provide technical and architectural leadership for the firm’s data platform, with a primary focus on building and operating modern, cloud based data foundations.
• Define and promote best practices for data engineering across the firm, including standards for code quality, testing, deployment, monitoring, and documentation.
• Design, implement, and maintain reliable processes for acquiring, consolidating, and organizing data from core systems and external sources, and making it available for downstream use.
• Ensure that data engineering solutions are scalable, maintainable, and reliable, including management of performance, availability, and capacity risks.
• Partner with Data Science & AI, Information Design & Engineering, IT Operations, and business leaders to understand challenges and translate them into data requirements and platform improvements.
• Contribute to data and AI governance by implementing and enforcing controls for data quality, lineage, access, and responsible use within the data platform.
• Lead the planning, deployment, and ongoing management of data engineering initiatives and related projects.
• Evaluate…