I’m a cross-functional software engineer with deep expertise across data engineering, ML/AI, Backend and iOS mobile development - building scalable, cloud-native systems from backend infrastructure and data pipelines to ML deployment and intuitive mobile experiences. 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: Design and maintain high-throughput ETL/ELT pipelines, batch processing, and real-time streaming workflows using Apache Spark, Kafka, Hadoop, Hive, Airflow, and DBT. Work extensively with cloud data platforms including Snowflake, BigQuery, Redshift, Azure Synapse, and Databricks. Proficient in advanced data modeling, SQL performance tuning, indexing, partitioning, clustering, and schema optimization. Handle structured, semi-structured, and unstructured data using Parquet, Avro, ORC, and JSON. 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: Build scalable microservices, backend APIs, and distributed systems using Python (FastAPI, Flask, Django), Java, and Go. Hands-on with relational and NoSQL databases such as PostgreSQL, MySQL, MongoDB, DynamoDB, and Elasticsearch. Leverage CI/CD tools like GitHub Actions, GitLab CI, Bitbucket Pipelines, Jenkins, Docker, and Kubernetes. Deploy cloud-native applications across AWS (EC2, Lambda, S3, RDS, Glue), GCP (GKE, Cloud Functions, Pub/Sub), and Azure (AKS, Logic Apps). Practice Agile, Scrum, TDD, and DevOps methodologies using JIRA, Confluence, and Slack. 𝐢𝐎𝐒 𝐌𝐨𝐛𝐢𝐥𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Build high-performance native iOS apps using Swift, SwiftUI, UIKit, Combine, CoreData, CoreLocation, MapKit, and AVFoundation. Implement MVVM, MVC, and VIPER architectures. Integrate with RESTful APIs, GraphQL, and Firebase. Use tools like Xcode, Fastlane, and TestFlight for mobile CI/CD, app distribution, and App Store deployment. Focus on UX, accessibility, responsiveness, and mobile security. 𝐀𝐈 / 𝐌𝐋 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: Develop and deploy ML/DL models using TensorFlow, PyTorch, Scikit-learn, Keras, XGBoost, LightGBM, and Hugging Face Transformers. Build systems for NLP, computer vision, time-series forecasting, and recommendation engines. Implement ML pipelines using MLflow, DVC, TFX, and Kubeflow. Deploy models via FastAPI, Docker, and Kubernetes, with observability through Grafana, and Evidently AI. Collaborative communicator who partners effectively with product, data, design, and engineering teams to deliver impactful, user-centered solutions driven by curiosity, innovation, and technical excellence.