- Design, build, and maintain scalable production data pipelines.
- Ingest, process, and transform large volumes of data from multiple sources.
- Develop solutions for data standardization, normalization, matching, and validation.
- Build data quality controls and monitoring to identify malformed, inconsistent, or incorrect data.
- Design reliable approaches to data corrections, updates, reprocessing, and backfills.
- Improve the architecture, scalability, reliability, and performance of the data platform.
- Take end-to-end ownership of technical solutions and production quality.
- Work closely with a small engineering team while independently driving your area of responsibility.
- Use AI-assisted engineering tools and practices to improve development efficiency.
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