Full-Time Senior Data Engineer

About the Role: We're seeking a Senior Data Engineer with expertise in MLOps Engineering to help drive model development and delivery best practices. You'll shape and implement automation across the machine learning lifecycle, from data collection to model training and monitoring.

Responsibilities:

• Operationalize key data science solutions for risk prediction products (underwriting, pricing, claims routing, marketing).
• Design and build ML pipelines using industry best practices, primarily on AWS services (SageMaker), integrating with MLflow and Snowflake.
• Stand-up and operate a shared feature store (Snowflake Snowpark + Kafka) supporting batch and real-time feature retrieval.
• Own real-time inference services with low-latency endpoints (SageMaker endpoints or EKS micro-services), managing deployments (blue/green or canary).
• Implement comprehensive testing strategies (unit, integration, data validation, model validation, performance) within robust CI/CD pipelines.
• Enable ML governance: manage model and data versioning, experiment tracking, and reproducibility.
• Implement event-driven orchestration for automated retraining, evaluation, and redeployment based on data drift or business events.
• Monitor production models for performance, drift, and data quality, driving automated remediation.

Qualifications:

• Bachelor's degree or equivalent experience
• 8+ years industry experience, with 2+ years focused on MLOps and 2+ years in software engineering.
• Strong Python and Docker skills.
• Familiarity with build tools (Bash, Bazel).
• Proficient in IaC principles and tools (Terraform).
• Experience designing, deploying, and managing scalable, resilient MLOps solutions on AWS.
• Expertise in the entire machine learning lifecycle (data ingestion, preprocessing, training, deployment, monitoring).
• Excellent written and verbal communication with a strong collaborative focus.
• Experience designing and implementing workflows using tools like AWS Step Functions.
• Experience with CI/CD tailored for machine learning systems.

Bonus Points:

• Experience in large-scale distributed systems, complex APIs, or platform-level software engineering.
• Snowflake's advanced ML capabilities (Snowpark, UDFs, external integrations).
• Insurance industry experience or experience in a highly regulated environment.

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