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 and prioritize data engineering work based on firm needs, strategic value, and available capacity.
• Manage and document projects, including scope, timelines, risks, dependencies, and key decisions.
• Establish and maintain effective relationships with key technology vendors and service providers that support the data platform.

POSITION-SPECIFIC REQUIREMENTS

• Bachelor’s degree in computer science, engineering, information systems, or related field, or equivalent industry experience; graduate degree preferred.
• At least 3–5 years of experience leading data engineering or closely related technical teams, including responsibility for setting direction, standards, and priorities.
• Experience managing budgets and making cost conscious decisions about tools, platforms, and services.
• Strong understanding of modern data engineering practices, including data ingestion, consolidation, transformation, and organization to support analytics and AI.
• Extensive experience with data management and data transformation, including performance, reliability, and scalability considerations.
• Advanced SQL experience and strong understanding of how to design and optimize data structures in relational and other data storage technologies.
• Experience designing and managing data solutions in modern cloud environments (for example, Microsoft Azure or Amazon Web Services), including use of platform services.
• Working knowledge of Python and common data tooling, with sufficient depth to review designs and solutions produced by engineers and to engage effectively with Data Science & AI teams.
• Demonstrated experience collaborating with data scientists, analysts, and AI practitioners, and understanding how engineering choices affect downstream analytics and AI work.
• Broad familiarity with data visualization, reporting, and application needs so that data platforms are designed with end to end use in mind, even when this role does not own the final experiences.
• Extensive experience with software development life cycle and software engineering best practices, including version control, testing, deployment, monitoring, and secure handling of data.
• Ability to define and implement data and platform standards, and to guide teams in adopting consistent, high quality engineering practices.

The above is intended to describe the general content of and requirements for the performance of this job. It is not to be construed as an exhaustive statement of essential functions, responsibilities, or requirements. The Firm will provide reasonable accommodations as necessary to allow an individual with a disability to apply for and/or perform the essential functions of a position. If you need assistance to accommodate a disability, please contact HR.

COMPENSATION AND BENEFITS

Employees are entitled to compensation commensurate with skill and experience. The exact compensation will vary based on skills, experience, location, and other factors permitted by law. The expected compensation ranges for this position in various states and jurisdictions are as follows:

• State of Colorado: $121,000 - $215,000
• State of Illinois: $119,000 - $230,000
• State of Maine: $89,000 - $206,000
• State of Maryland: $127,000 - $193,000
• State of Massachusetts: $131,000 - $251,000
• State of Minnesota: $131,000 - $217,000
• Jersey City, NJ: $143,000 - $258,000
• State of New York: $122,000 - $264,000
• State of Vermont: $130,000 - $249,000
• State of Virginia: $85,000 - $249,000
• State of Washington: $127,000 - $242,000
• Washington, D.C.: $169,000 - $249,000

Full-time employees receive benefits including:

• medical and dental coverage
• life insurance
• short-term disability insurance
• long-term disability insurance
• pre-tax flexible spending account for certain medical and dependent care expenses
• an employee assistance program
• Paid Time Off
• paid holidays
• participation in a retirement plan program after meeting eligibility requirements
• and more

EOE/Minority/Female/Disabled/Vet. Principal Applicants Only.

Qualifications

Education

Required

Bachelors or better in Computer Science or related field.

Experience

Required

3-5 years:

Experience leading data engineering or closely related technical teams, including responsibility for setting direction, standards, and priorities.

Experience managing budgets and making cost conscious decisions about tools, platforms, and services.

Extensive experience with data management and data transformation, including performance, reliability, and scalability considerations.

Advanced SQL experience and strong understanding of how to design and optimize data structures in relational and other data storage technologies.

Experience designing and managing data solutions in modern cloud environments (for example, Microsoft Azure or Amazon Web Services), including use of platform services.

Demonstrated experience collaborating with data scientists, analysts, and AI practitioners, and understanding how engineering choices affect downstream analytics and AI work.

Broad familiarity with data visualization, reporting, and application needs so that data platforms are designed with end to end use in mind, even when this role does not own the final experiences.

Extensive experience with software development life cycle and software engineering best practices, including version control, testing, deployment, monitoring, and secure handling of data.

Preferred

Working knowledge of Python and common data tooling, with sufficient depth to review designs and solutions produced by engineers and to engage effectively with Data Science & AI teams.

Equal Opportunity Employer
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