Feature Engineer / ML Data Engineer

Role Feature Engineer / ML Data Engineer

Location Cleveland, OH | Pittsburgh, PA | Dallas, TX (Onsite)

Fulltime

Job Description

Must Have Technical/Functional Skills:

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

Job Description:

Design and implement scalable, reusable feature pipelines (batch and real-time)

Develop complex feature transformations and advanced data modelling 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

Roles & Responsibilities

Technical Skills

Programming: Advanced Python and SQL

Distributed Processing: Spark / Flink (large-scale data processing)

Feature Engineering: Advanced transformations, feature design patterns

Data Modelling: Complex transformations, aggregation strategies

Feature Stores: Hands-on with platforms such as Hops works, 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 / GCP)

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