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As a Data Engineer, I build and manage robust, end-to-end data systems designed for scalability and real-time performance. My experience covers the full data lifecycle: from automated data scraping and ingestion, through complex batch and stream processing, to the development of custom APIs and customer-facing analytical applications. I am proficient in cloud-native environments, leveraging containerization and orchestration to create resilient, microservice-based architectures. I focus on writing clean, efficient code and selecting the best technologies to solve complex data challenges in a practical and maintainable way. Technical Expertise Data Streaming & Real-Time Processing: Apache Kafka: Fluent in designing and operating high-throughput streaming platforms, including Confluent Kafka and Kafka Connect (Source/Sink connectors) deployed on Kubernetes. Apache Flink: Development of stateful, real-time stream processing applications. Apache Spark: Building and optimizing Spark Structured Streaming pipelines. Batch Processing & Big Data: Apache Spark: Extensive experience in large-scale batch ETL processing using PySpark across diverse data sources. Big Data Ecosystem: Proficient with Databricks, Hadoop, and Apache Hive. Data Orchestration & Workflow Automation: Apache Airflow: Designing, scheduling, and monitoring complex DAGs. Specialized experience using the KubernetesPodOperator for scalable, containerized task execution within Rancher-managed clusters. Apache NiFi: Building and managing automated data flows. Cloud, Containerization & DevOps: Cloud Platforms: AWS (S3, Redshift, Glue, Athena), GCP. Containerization: Docker, containerd. Orchestration: Kubernetes (K8s), including hands-on experience with minikube and k3s, managed via Rancher. Architecture: Designing and implementing Microservice Architectures. CI/CD: Jenkins, GitHub Actions, Git (GitHub, Bitbucket), version control, and branching strategies. Databases & Data Warehousing: NoSQL: Cassandra (daily operational use in production clusters), MongoDB, CouchDB. Analytical (OLAP): ClickHouse, Trino (PrestoSQL), Amazon Redshift. Relational (SQL): PostgreSQL, MySQL. Storage & Caching: Redis for application caching layers, MinIO for S3-compatible object storage. API Development & Embedded Analytics: API Development: Building performant web services and APIs using FastAPI and Python. Proficient with API testing tools like Postman. Embedded Analytics: Advanced development with Apache Superset, utilizing its REST API and Security API to build secure, custom shell applications for customer-facing analytics. Monitoring, Logging & Visualization: Log Management: Full implementation of the ELK Stack (Elasticsearch, Logstash, Kibana) for log aggregation, analytics, and building monitoring dashboards. Metrics & Visualization: Grafana, Tableau, Power BI, Apache Superset. Programming, MLOps & Project Management: Languages: Python (incl. Pandas, NumPy), SQL, Bash. MLOps: MLflow for managing the machine learning lifecycle. Project Management: Atlassian Jira for Agile/Scrum sprint planning and task management. Data Scraping: Designing and operating automated data scraping pipelines using Puppeteer, Selenium, Playwright, and FlareSolverr. Notable Projects - Reddit Data Pipeline Developed an automated pipeline for extracting, transforming, and analyzing Reddit data. Leveraged NiFi, MinIO, Trino, and Tableau/Superset for a complete ETL process, enabling dynamic querying and visualization of high-velocity data streams. - OTP Data Pipeline Engineered a real-time pipeline for secure OTP generation and notifications, utilizing Kafka, Airflow, Cassandra, and MongoDB. Integrated email and Slack/Discord notifications for streamlined monitoring. - Yelp Sentiment Analysis Created a real-time streaming pipeline for Yelp reviews using Spark, Kafka, and Hugging Face’s DistilBERT. Visualized sentiment analysis insights in Kibana, showcasing the integration of machine learning with data engineering. - ELK Stack Log Management Set up a secure and scalable multi-node ELK Stack for log analytics, employing index lifecycle policies and creating drill-down dashboards in Kibana. Certifications and Education - IBM Data Engineering Specialization (Coursera) - Apache Kafka, ELK Stack, and NoSQL Databases (BTK Academy) - Machine Learning Specialization (Stanford, Coursera) - Data Engineering Nanodegree (Udacity)

Full-stack software developer with 15+ years' experience, design acumen, and a keen eye for UX and simplicity. Proven track record in getting things done. Specialize in web and mobile apps. Proficient in AWS, G Cloud, React, Java and more. Diverse project background. Highlighted achievements from my resume include: 1. Spearheaded the development of an EV-charging SaaS platform. 2. Orchestrated the migration of PL/SQL business logic to Spring Boot microservices at Allianz. 3. Pioneered the creation of a cutting-edge eCommerce recommendation system. 4. Elevated customer satisfaction with innovative design on a municipality helpline software. 5. Developed a reputation management web app utilizing G Cloud, Quarkus, Vue.js, and Firebase.

Turn messy, complex data into reliable, scalable, and production-ready systems. I am a Data Engineer and Architect with over 5 years of experience specializing in the entire data lifecycle. From building real-time streaming architectures to deploying cost-efficient cloud analytics platforms, I bridge the gap between raw data and actionable business value. With a background in both Data Engineering and Data Science, I don't just move data; I ensure it is modeled for high-performance analytics and predictive insights. Core Expertise & Services: • Data Warehouse & Lakehouse Architecture: Custom-designed, scalable solutions using Databricks (Delta Lake), and BigQuery. • ETL/ELT Pipeline Development: Robust data workflows using Python, SQL, dbt, and Apache Spark. Real-Time Streaming: High-performance systems utilizing Kafka, Flink, and Spark Streaming (Scala/Python). • Orchestration & MLOps: End-to-end workflow automation with Apache Airflow; production-grade MLOps pipelines using MLflow for experiment tracking and model lifecycle management; CI/CD pipelines with Jenkins, GitHub Actions, Terraform, and Helm. Real-time change data capture (CDC) architectures with Debezium integrated into Kafka-based systems. • Infrastructure & DevOps: Production-ready containerization via Docker & Kubernetes across AWS, GCP, and Azure, or specialized on-premises environments. • Database Migrations: Seamless metadata upgrading and migration for PostgreSQL, MySQL, and NoSQL systems. • AI Engineering & LLMOps: Building production-ready LLM-based systems, RAG architectures, and vector data modeling integrated with MLflow for scalable AI deployment. • AI-Driven Automation & Orchestration: Designing and deploying autonomous AI agents and advanced workflow automation using n8n. Expert in bridging LLMs, vector databases, and enterprise data pipelines into production-ready, self-hosted or cloud-based autonomous systems that orchestrate complex business logic. Technical Stack: Languages: Python (FastAPI), Scala, SQL. Big Data Tools: Spark, Trino, Flink, Hadoop, Hive. Data Ops, MLOps & Automation: Airflow, dbt, n8n (AI Agent Workflows), Kafka, Debezium (CDC), MLflow, Jenkins, CI/CD pipelines. Cloud: AWS, GCP, Azure, MinIO. Monitoring & Logging: Elasticsearch, Kibana Visualization: PowerBI, Tableau, Looker Studio Proven Impact: Award-Winning Solutions: Led a freight price estimation project that achieved 78% accuracy, winning the Ministry of Trade Digital Transformation Award. Cost Efficiency: Reduced annual operational costs by $150K through optimized data architecture and predictive modeling. Global Collaboration: Extensive experience working with international teams across Europe and Turkiye, combining technical leadership with business strategy. Whether you need a complete migration to the cloud or a real-time analytics dashboard, I am here to build the engine that powers your growth. Let's discuss how I can optimize your data infrastructure and unlock valuable insights for your business. Click "Invite to Job" or "Message" to start the conversation!

I deliver comprehensive, end-to-end solutions that bridge the gap between complex software development and resilient infrastructure, ensuring your systems are scalable, secure, and mission-ready. Languages, Frameworks & Core Architecture • Java, Kotlin, Go, Python, Node.js, Typescript, Bash scripting. • Backend Frameworks: Spring Boot (Cloud, Stream, Security, Data), Express, Mongoose. • Frontend : React , NextJs, AntDesign, • Architectural Patterns: Event-Sourcing, Pub-Sub, Monolith-to-Microservices DataOps & Distributed Storage • Message : Kafka, Kafka Streams, RabbitMQ (Shovel, DLQ, TTL), SQS, SNS • Databases & In-Memory: PostgreSQL, EDB (EnterpriseDB), PgPool, Apache Ignite, Redis, DynamoDB. Cloud, Infrastructure & Orchestration • DevOps Engineering: High-Scale Cloud-Native Infrastructure, GitOps. • Kubernetes Ecosystem: Production Cluster Management, Rancher RKE2, Custom Kubernetes Operators, Helm Charts, EKS, GKE, AKS, OpenShift. • Infrastructure as Code (IaC): Terraform, Ansible. • CI/CD Pipelines: GitHub Actions, Jenkins, ArgoCD. • Observability & Monitoring: Prometheus, Grafana, Custom Infrastructure Alerting.