- Proficiency in pipeline orchestration tools (e.g., Dagster, Airflow)
- Strong Python programming skills with experience in libraries like Pandas and PySpark
- Expertise in cloud platforms, particularly AWS (e.g., S3, Lambda, Redshift, RDS)
- Deep understanding of data modeling, ETL workflows, and scalable architecture design
- Familiarity with integrating machine learning models into production workflows
- 3+ years of experience in a Data Engineering role, with experience in mid-to-senior capacity
- Proven track record of working with live datasets and building end-to-end data pipelines
- Strong SQL skills for querying and managing large datasets
- Hands-on experience in creating architectural diagrams and delivering technical presentations
- Experience in building and optimizing propensity models or similar predictive analytics models
- Strong understanding of feature engineering, predictive modeling, and evaluation metrics
- Experience with version control tools (e.g., Git) and CI/CD pipelines