Sr. Data Engineer I
Core
Designing and building scalable data pipelines, architectures, and MLOps platforms to support production-grade AI/ML initiatives and a modern data ecosystem.
Role type
Senior Data Engineer (MLOps focus)
Builds
Cloud-native data lake, data warehouse, and machine-learning enablement platforms
Domain
E-commerce / Health & Wellness / Cloud Data Engineering
Deliverable
production ML models | infrastructure
Required skills
Data modeling, PySpark, Python, SQL, RESTful API development, CI/CD implementation, Docker containerization, ML tooling (MLflow, SageMaker, Kubeflow), Cloud data warehousing (Databricks, S3, Redshift, BigQuery)
Preferred skills
Master's degree in technical discipline, AWS certifications (DevOps, Solutions Architect, Data Analytics, Security), experience with Master Data Management (MDM)
Technologies
Databricks, PySpark, Python, SQL, MLflow, SageMaker, Kubeflow, Docker, AWS, S3, Redshift, BigQuery
Responsibilities
Design and implement data architectures and applications for speed and efficiency; Partner with data scientists to build reproducible ML pipelines including feature engineering and model deployment; Implement CI/CD for data and ML workflows; Build production-grade ML infrastructure like feature stores and model registries; Design scalable data pipelines for batch, streaming, and real-time inference; Establish MLOps standards and automation patterns.
Seniority
Senior, hands-on IC