Sr. Feature Engineer
Dallas,TX/ Pittsburgh, PA / Clevland OH
Full-Time
Tech:
Data Engineering/Pipeline
MLOps Engineering/Pipeline
OpenShift
Git
Linux
Programming language:
Python
SQL
Spark
Hive
Title Job Description Skillsets Typical Experience
Feature Engineer (Sr) • Design and implement scalable, reusable feature pipelines (batch and real-time)
• Develop complex feature transformations and advanced data modeling logic
• Optimize feature performance, latency, and cost efficiency
• Ensure feature quality, validation, and SLAs (freshness, accuracy, reliability)
• Collaborate with Data Science and ML Engineering teams to align features with use cases
• Contribute to feature store architecture and standards
• Mentor Feature Engineers and promote engineering best practices
• Support production deployment, monitoring, and incident resolution
Technical Skills
· Programming: Advanced Python and SQL
· Distributed Processing: Spark / Flink (large-scale data processing)
· Feature Engineering: Advanced transformations, feature design patterns
· Data Modeling: Complex transformations, aggregation strategies
· Feature Stores: Hands-on with platforms such as Hopsworks, Feast, SageMaker
· ML Lifecycle Understanding: Feature importance, model input optimization
· Data Quality & Validation: Drift detection, validation frameworks
Platform & Engineering
· CI/CD pipelines and automated testing
· Cloud platforms (Azure / AWS / Google Cloud Platform)
· Monitoring, observability, and production debugging
· Performance tuning and scalability optimization
Soft Skills
· Technical leadership and mentoring
· Cross-team collaboration (Data Science, MLOps, Platform)
· Strong problem-solving and optimization mindset
· Ability to translate business use cases into feature logic
• 3–10+ years in Data Engineering, Feature Engineering, or ML Engineering
• Proven experience designing production-grade data/feature pipelines
• Strong track record in scalable distributed data systems
• Experience working in enterprise AI/ML platforms or feature stores
• Prior mentoring or technical leadership experience
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