Keller Postman needs to design, construct, install, test, and maintain highly scalable data management systems to support their litigation and arbitration efforts, driving innovation in the practice of law and pursuing unparalleled excellence.
Requirements
- 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.
- 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).
Responsibilities
- 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.
- Support CI/CD pipelines and automation for data workflows and deployments.
Other
- 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.
- 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.
- Must be able to read, write, and speak fluent English.
- A minimum of 5 years of experience in a data engineering role.
