Senior Feature Engineer- Hadoop

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