Machine Learning Engineer

Overview

Key Responsibilities
• Design, build, and maintain scalable ETL/ELT pipelines to support analytics and machine learning workloads.
• Develop and manage robust data models and warehouse structures that support self-service analytics and reporting.
• Work with stakeholders across the business to understand data requirements and ensure data availability, accuracy, and usability.
• Implement and monitor data quality and validation checks to maintain trust in our data assets.
• Collaborate closely with data science and analytics teams to ensure data infrastructure supports model training and deployment.
• Optimize data storage and query performance across cloud-based and relational systems.
• Stay current with emerging data engineering tools and architectures and advocate for best practices across the team.

Required Qualifications
• 5+ years of experience in data engineering, data infrastructure, or related fields.
• Proficiency in SQL and at least one programming language (e.g., Python, Java, Scala).
• Experience working with cloud data platforms (e.g., AWS Redshift, Snowflake, BigQuery).
• Strong knowledge of data modeling, data warehousing, and building ETL/ELT pipelines.
• Familiarity with modern data orchestration tools (e.g., Airflow, dbt).
• Excellent communication and collaboration skills.

Preferred Qualifications
• Experience with real-time data streaming technologies (e.g., Kafka, Kinesis).
• Familiarity with CI/CD for data pipelines and infrastructure-as-code (e.g., Terraform).
• Experience supporting machine learning workflows and model deployment.
• Background in insurance, financial services, or other highly regulated industries.

Company:

Goosehead Insurance Agency

Qualifications:

Language requirements:

Specific requirements:

Educational level:

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Data Warehouse, Industry, Machine Learning, NLP, United States