Data Engineer
Core
Design and run data and ML pipelines enabling Marketing, Purchasing, Logistics, and Finance teams to make data-driven decisions.
Role type
Senior Data Engineer (ML Infrastructure)
Builds
Scalable ETL/ELT pipelines, data models, and MLOps infrastructure for production ML workflows.
Domain
eCommerce, Data Engineering, Machine Learning
Deliverable
production ML models
Required skills
SQL optimization, Python, Pipeline orchestration (Airflow, dbt, AWS Glue), Cloud platforms (GCP), Data modeling, MLOps, CI/CD, Docker
Preferred skills
Event streaming (Kafka, Kinesis), ML platforms (SageMaker, Vertex AI, Databricks), BI tools (Looker, Tableau)
Technologies
BigQuery, Snowflake, GCP, Airflow, dbt, AWS Glue, Python, SQL, Kafka, Kinesis, Docker, Git, CI/CD
Responsibilities
Design and maintain ETL/ELT pipelines handling 10M+ daily events; Develop and optimize data models for analytics and ML training; Build underlying features and data inputs for ML models; Develop and refine ML models for business use cases (sentiment, churn, forecasting); Establish and maintain MLOps pipelines for model deployment and monitoring; Implement data quality, security, and governance best practices.
Seniority
Senior, hands-on IC
