I am a Data Engineer and MLOps Platform Specialist focused on building high-throughput, distributed data platforms, scalable ETL pipelines, and machine learning infrastructure. My expertise lies in designing robust lakehouse architectures (Delta Lake, Lakefs), orchestrating complex workflows (Apache Airflow), and engineering production-grade ML pipelines.
Experienced in implementing healthcare interoperability gates (ABDM compliance), real-time vital signal streaming analytics, and deep learning clinical ensembles (FT-Transformers, Bi-LSTM temporal models) with automated cloud retraining triggers.
Python • Scala • SQL (PostgreSQL, MySQL, SQLite) • Java • TypeScript • Go • Bash
Apache Spark • PySpark Streaming • Delta Lake • Apache Iceberg • Dremio • Snowflake • Apache Airflow • Databricks • Apache Hadoop • Data Quality (Great Expectations)
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Scikit-learn • PyTorch • TensorFlow • TabPFN • Kaggle API • Hugging Face Hub • Conformal Prediction
AWS (EMR, S3, EC2, RDS, IAM) • Docker • Kubernetes • MinIO / HDFS • AutoSys • GitHub Actions CI/CD • Pinecone / SimpleVectorStore • Allembic / migrations
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Python, PySpark Streaming, Airflow, Delta Lake, FastAPI, Docker, Kubernetes, AWS
- Built an end-to-end data platform for 250k+ clinical records using Apache Airflow and PySpark pipelines, staging data in partitioned Delta Lake tables.
- Implemented automated cloud retraining triggers via Kaggle API and model weight synchronization with a private Hugging Face dataset hub.
- Developed a FastAPI service with a local vector retrieval index (
turbovecSIMD), JWT auth, and FHIR R4 clinical compliance serializers.
Python, PySpark, Airflow, Delta Lake, Redis, ONNX Runtime, FAISS, FastAPI, Docker
- Engineered a causal movie recommendation engine using PySpark Medallion pipelines for ETL and feature store curation.
- Developed a real-time clickstream feedback loop using Redis streams to update user sequential states asynchronously (sub-10ms latency).
- Implemented an adaptive serving API with hardware-aware fallbacks (NVIDIA GPU ensembling, quantized ONNX CPU, and SIMD vector index search).
- 💼 LinkedIn: Connect with Pavan Badempet on LinkedIn to discuss data engineering opportunities.
- ✍️ Blog & Portfolio: Visit Pavan's Data Engineering Portfolio and Blog for system architecture guides and big data tutorials.
- 💬 Stack Overflow: View the Pavan Badempet Stack Overflow Profile to see community Q&A contributions.
- 📮 Get in Touch: Shoot me an email or open an issue on any of my active repositories!
🔍 Career Keywords & Technical Index (SEO)
This profile indexes major industry domains and systems: Core Specializations: Data Platform Architect, Big Data Engineer Portfolio, MLOps Pipelines, Python and Scala Developer, AWS Solutions, Lakehouse Architect. Distributed Platforms: Apache Spark, PySpark Streaming, Delta Lake, Apache Airflow, Databricks, Data Lakehouses, PySpark ETL. AI Infrastructure & Inference: FT-Transformer models, TabPFN models, PyTorch Tabular MLP ensembles, conformal prediction bounds, Hugging Face Hub, Kaggle API integration. Compliance & Health Informatics: Ayushman Bharat Digital Mission (ABDM) gateways, FHIR standards, vital signals streaming.