Data quality and monitoring jobs

Senior MLOps Engineer (Data & ML Platform)

SD Solutions · Posted Nov 13, 2026

Own the data that Falcon’s offer-ranking model learns from: the raw sources, the pipelines, the training tables, and the monitoring around them.

Own the ML data pipelines: build and run batch pipelines on Spark and Databricks, from raw data to feature and training tables, including enrichment and backfills for late-arriving data.
Onboard new data sources: bring in internal databases, external APIs, partner feeds and web data, and match them to Falcon’s own entities.
Use LLMs inside pipelines: add LLM steps to batch jobs, such as turning text into embeddings and structured attributes.
Keep training and serving consistent: make sure features match between training and the live inference service, which includes reading its Java code.
Monitor data and model inputs: run scheduled data quality checks and Grafana alerts that catch bad data before it reaches the model, and find the root cause when something breaks.