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Principal Data Engineer | 12+ Years Of Experience | Big Data, Streaming and Analytics

Actively Looking for Work

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Principal Data Engineer

Principal Data Engineer with over 12 years of experience architecting, building, and scaling petabyte-scale data and AI platforms that enable data-driven decision-making, advanced analytics, personalization, and sustainable business growth. I specialize in designing modern data architectures that power real-time and batch processing systems across high-volume, distributed environments. My expertise spans distributed systems, streaming architectures, large-scale data lakes and warehouses, and low-latency serving infrastructure for machine learning applications.

Key Achievements

  • I have led the design and implementation of real-time feature stores, embedding generation pipelines, and vector database platforms supporting large-scale semantic search and recommendation systems.
  • My work includes building resilient data pipelines that process billions of events per day with strong guarantees around reliability, scalability, and observability.
  • I have deep experience optimizing storage, compute, and data access patterns to ensure cost efficiency while maintaining high throughput and low latency.

AI/ML Focus

In the AI/ML domain, I focus on production-grade ML infrastructure, enabling real-time inference for fraud detection, anomaly detection, experimentation platforms, and personalized recommendations. I have partnered closely with data scientists, ML engineers, and product teams to translate research models into scalable, fault-tolerant systems that operate under strict latency and availability requirements.

  • My experience includes model serving architectures, feature engineering pipelines, online/offline consistency strategies, and A/B experimentation frameworks.

Additional Contributions

Beyond technical execution, I have driven platform strategy, defined architectural standards, mentored engineering teams, and influenced long-term technical roadmaps. I am passionate about building extensible, self-service data platforms that empower organizations to innovate rapidly while maintaining governance, security, and data quality at scale.

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