Data Engineer
Core
Design and run data and ML pipelines enabling Marketing, Purchasing, Logistics, and Finance teams to make data-driven decisions.
Role type
Data Engineer with ML pipeline focus
Builds
Scalable ETL/ELT pipelines, data models, and MLOps infrastructure for analytics and ML training
Domain
eCommerce, data engineering, machine learning
Deliverable
production ML models | product features | dashboards & analysis
Required skills
SQL optimization, pipeline orchestration (Airflow, dbt, AWS Glue), Python, cloud data platforms (GCP), software engineering best practices (Git, CI/CD, Docker)
Preferred skills
event streaming (Kafka, Kinesis), ML platforms (SageMaker, Vertex AI, Databricks), BI tools (Looker, Tableau)
Technologies
BigQuery, Snowflake, Airflow, dbt, AWS Glue, GCP, Kafka, Kinesis, SageMaker, Vertex AI, Databricks, Looker, Tableau
Responsibilities
Design and maintain ETL/ELT pipelines handling 10M+ daily events; develop and optimize data models for analytics and ML; build underlying features and data inputs for ML models; establish and maintain MLOps pipelines for model deployment and monitoring; implement data quality, security, and documentation best practices; contribute to AI and LLM experiments for business problem solving
Seniority
Mid-level to Senior, hands-on IC
