Machine Learning Engineer
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
Senior (5+ years of experience)
Tagged as: Data Warehouse, Industry, Machine Learning, NLP, United States
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