Data Engineer

Keller Postman represents a broad array of clients in class and mass actions, individual arbitrations, and multidistrict litigation matters at the trial and appellate levels in federal and state courts. Serving hundreds of thousands of clients in litigation and arbitration, we have prosecuted high-profile mass tort, antitrust, privacy, product liability, employment, and consumer-rights cases. Our firm also acts as plaintiffs’ counsel in high-stakes public-enforcement actions. Our mission is to achieve exceptional results for our clients, drive innovation in the practice of law, and pursue unparalleled excellence in everything we do.

Purpose: The Data Engineer will play a critical role in our organization, focusing on the design, construction, installation, testing, and maintenance of highly scalable data management systems. This role requires hands-on expertise using Snowflake, Azure Cloud services, and Sigma to design, develop, and maintain scalable data pipelines and analytics solutions. The ideal candidate will have strong experience in cloud-based data architectures, modern ETL/ELT practices and technical expertise to support and improve current data systems and processes, as well as the ability to work collaboratively with cross-functional teams.

This is a remote position, but the ideal candidate will be on Central Standard Time or willing to work regular Central Standard Business hours; being located in the Chicago area is a plus. The compensation for this position is $130,000 to $150,000 per year, depending on experience, plus a year-end discretionary bonus and benefits.   

Essential Functions:

• Develop, construct, test, and maintain data architectures, including databases and large-scale processing systems.
• Design, build, and optimize data pipelines and ETL/ELT processes leveraging Snowflake and Azure Services.
• Develop and maintain Snowflake data warehouses, ensuring efficient data modeling, partitioning, and performance tuning.
• Implement data flow processes that automate and streamline data collection, processing, and analysis.
• Ensure data governance, quality, and security best practices across all data platforms.
• Collaborate with analytics and business teams to improve data models that feed business intelligence tools, increasing data accessibility and fostering data-driven decisionmaking across the organization.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
• Provide operational support for existing data infrastructure and develop new solutions as needed.
• Monitor, troubleshoot, and optimize system performance in Azure and Snowflake environments.
• Support CI/CD pipelines and automation for data workflows and deployments.
• Keep current with industry trends and innovations in data engineering and propose changes to the existing landscape.

Knowledge, Skills, Abilities:

• Proficient in Snowflake, Databricks, or similar tools and experience in data warehousing.
• Skilled in SQL, ETL design, and data modeling.
• Proficiency in SQL (complex queries, stored procedures, optimization) and familiarity with Python for data engineering tasks.
• Experience with Salesforce data integration is a plus.
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Strong knowledge of ETL/ELT patterns, orchestration, and workflow automation.
• Familiarity with Sigma Computing for reporting, data visualization, and business user self-service analytics.
• Understanding of data governance, security, and compliance frameworks (e.g., GDPR, HIPAA).
• Experience with streaming data technologies (Kafka, Event Hubs, or similar).
• Exposure to DevOps practices and Infrastructure as Code (e.g., Terraform, ARM templates).
• Adept at queries, report writing, and presenting findings.
• Excellent problem-solving and troubleshooting skills.
• Ability to work in a fast-paced environment and manage multiple projects simultaneously.
• Strong communication skills, capable of conveying complex data issues to non-technical team members.

Education/Experience:

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field.
• A minimum of 5 years of experience in a data engineering role.
• Experience working with Azure cloud services and data warehousing technologies.
• Relevant certifications in Azure or other cloud technologies are beneficial.

Language Ability:

• Must be able to read, write, and speak fluent English