Related skills
azure aws python gcp databricks📋 Description
- Design data-heavy components of ML infra for real-time decisions.
- Build distributed data pipelines for training and feature engineering.
- Optimize Feature Store to align training and production data.
- Act as a technical consultant to data scientists with Spark tooling.
- Expand ML data infrastructure for scalable ingestion and transformation.
- Improve MLOps standards: reproducibility, lineage, quality.
🎯 Requirements
- 5+ years large-scale data processing; Apache Spark.
- 5+ years developing complex software in Python or Scala.
- Backend and server-side development on scalable systems.
- Data Engineering patterns: partitioning, sharding, schema evolution.
- Experience with AWS, GCP, and Azure.
- Kafka streaming and Databricks/Airflow for ML workflows.
🎁 Benefits
- Great Place to Work Certification (2021-2023).
- Fortune’s Best Workplaces in NYC (2022).
- Fast Company’s Most Innovative Finance Companies (2022).
- Forbes Cloud 100 (2021-2022).
- SAP Pinnacle Awards – New Partner Application Award (2023).
- Fintech Breakthrough Awards – Best Fraud Prevention Platform (2023).
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