Sr. Data Engineer I
Core
Designing and building scalable data pipelines, data models, and MLOps infrastructure to support production-grade AI/ML initiatives and a modern data ecosystem.
Role type
Senior Data Engineer (MLOps focus)
Builds
Cloud-native data platforms, data lakes, warehouses, and operationalized ML pipelines
Domain
E-commerce / Health & Wellness / Data Engineering & MLOps
Deliverable
production ML models | infrastructure
Required skills
PySpark, Python, SQL, data modeling, RESTful APIs, Docker, CI/CD, MLflow, SageMaker, Databricks, feature engineering, model monitoring
Preferred skills
AWS certifications, Master Data Management (MDM), experiment tracking, model lifecycle management
Technologies
Databricks, S3, Redshift, BigQuery, PySpark, Python, SQL, MLflow, SageMaker, Kubeflow, Docker, AWS
Responsibilities
Design and build scalable data extracts, integrations, transformations, and data models; Deploy and provision data solutions across environments; Implement data architectures enabling speed, quality, and efficiency; Partner with data scientists to design, build, and maintain reproducible ML pipelines; Implement CI/CD for data and ML workflows; Build and maintain production-grade ML infrastructure (feature stores, model registries); Ensure ML models follow best-practice governance and monitoring; Design scalable data pipelines for batch, streaming, and real-time inference; Establish MLOps standards and automation patterns
Seniority
Senior, hands-on IC
