Data Engineer II

📋 Description

• Design, build, and optimize ETL pipelines powering analytics and ML workflows.
• Develop labeling and retraining pipelines for ML models with quality and observability.
• Implement MLOps practices: model versioning, CI/CD for ML, model monitoring.
• Collaborate with data scientists to productionize training, inference, and evaluation.
• Contribute to data lakehouse design: schema, partitioning, performance.
• Document data architecture, lineage, and dependencies for transparency.

🎯 Requirements

• Bachelor’s degree in CS/Engineering or related field.
• 2–4 years building/operating large-scale data systems for analytics/ML.
• Proficiency in Python and SQL; experience with PySpark, pandas.
• Experience with DBT.
• Experience with modern data warehousing/lakehouse platforms, preferably Databricks.
• Hands-on with orchestration tools like Airflow, Dagster, or Prefect.

🎁 Benefits

• Competitive pay, health insurance, 401(k) matching, equity plan.
• Flexible time off, holidays, parental leave, year-end break.
• Work-from-home funds and wellness benefits to support growth and wellbeing.