Data Engineering Manager - Cloud Platform Lead (Remote)

Husch-Blackwell-LL; Austin (TX); Hybrid; USD 150,000 - 230,000; Full time

Job summary

Husch Blackwell LLP is seeking a Data Engineering Manager to design and build a cloud-based data platform that enables analytics, reporting, and AI across the firm.

The role leads Data Engineering staff, sets standards, and collaborates with Data Science & AI teams to deliver scalable, secure data services for multiple stakeholders. Remote or hybrid options are available in supported time zones.

Qualifications

• Bachelor’s degree in CS or related field (graduate degree preferred).
• 3–5 years leading data engineering or related teams.
• Experience managing budgets and cost decisions for tools/services.
• Strong understanding of modern data engineering for analytics/AI.
• Advanced SQL and data structure design in relational/non-relational stores.
• Experience designing data solutions in cloud environments (Azure/AWS).
• Collaborating with data scientists, analysts, and AI practitioners.

Responsibilities

• Supervising all Data Engineering staff.
• Provide technical and architectural leadership for the data platform.
• Define and promote best practices for data engineering across the firm.
• Partner with Data Science & AI teams to translate data requirements.
• Design, implement, and maintain data ingestion, consolidation, and organization processes.
• Plan and manage data engineering initiatives and projects.
• Ensure scalability, reliability, and security of data platforms.

Skills

Leadership

Data engineering

SQL

Python

Cloud computing

Data governance

Communication

Stakeholder management

SDLC

Education

Bachelor's degree in CS or related

Graduate degree preferred

Tools

Azure

AWS

ETL tools

Data warehouses

Job description

Husch Blackwell LLP is seeking a Data Engineering Manager to design and build a cloud-based data platform that enables analytics, reporting, and AI across the firm.

The role leads Data Engineering staff, sets standards, and collaborates with Data Science & AI teams to deliver scalable, secure data services for multiple stakeholders. Remote or hybrid options are available in supported time zones.