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Pavanika Thotakura
Senior Data Engineer specializing in cloud big data pipelines and real-time streaming
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Amazon data engineer who built a real-time fraud detection pipeline for AWS Lambda, tackling multi-region telemetry quality issues and scaling stream processing for billions of daily requests. Strong in production-grade data/ML workflows on AWS (EMR, Glue, Kinesis, SageMaker) with hands-on entity resolution and anomaly detection.
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Key Strengths
- Built fraud detection pipeline for AWS Lambda processing billions of requests/day
- Designed data quality layer for inconsistent multi-region telemetry logs (schema validation, null handling, timestamp standardization, outlier filtering)
- Implemented automated schema-change checks/alerts in AWS Glue to prevent upstream breaks
- Scaled real-time processing using AWS Kinesis with parallelization and resource optimization to reduce latency
- Entity resolution across multi-source logs using standardized keys, timestamp normalization, and fuzzy matching (Levenshtein distance)
- Pragmatic ML delivery: moved from experimentation to production based on baseline performance, feature stability, and business alignment; added monitoring and CI/CD
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Senior Data Engineer specializing in cloud data pipelines and real-time streaming
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