Related skills
bigquery redshift python airflow pyspark📋 Description
- Design, build, and scale real-time and batch data pipelines for retail media.
- Use Python, Spark, and streaming frameworks to process data.
- Contribute to MLOps: scalable infra, model deployment, monitoring.
- Collaborate with data scientists, analysts, lead engineers, and PMs.
- Focus on reliability, scalability, and performance of data/ML infra.
- Mentor junior engineers; advocate data engineering and MLOps best practices.
🎯 Requirements
- 7-9 years in data engineering.
- SQL, PySpark, Hive.
- Argo Workflows and Airflow.
- Redshift or BigQuery; GCP or Azure.
- Python, FastAPI; Git; unit testing.
- Reliability: logging, monitoring, alerts; mentoring.
🎁 Benefits
- Flexible working hours.
- Birthday off.
- Investment in cutting-edge tech.
- Inclusive, diverse culture with active networks.
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