DATA ENGINEER- MICROSOFT CERTIFIED With over 8 years of expertise in crafting end-to-end data solutions, I excel in designing and optimizing data pipelines for analysis, predictive modeling, and ETL within agile frameworks. Proficient in Python, SQL, Java, and diverse technologies such as PySpark and Kafka, I specialize in data warehousing (Redshift, Snowflake) and automation with Airflow and Dagster. Skilled in cloud-based deployments (AWS, Azure), data quality assurance (CDC, SCD, incremental loading), and serverless architecture, I leverage CI/CD pipelines and DevOps practices to enhance scalability and performance, ensuring seamless integration

I empower businesses through data by transforming chaotic raw data into structured, production-ready architectures. As an Analytics Engineer and Data Analyst, I specialize in the Modern Data Stack, utilizing dbt and Google BigQuery to build resilient data pipelines that emphasize quality and performance. My experience includes implementing dual-layer data quality checks with dbt schema tests and tailored Python auditing scripts, ensuring data integrity at every stage. My approach is grounded in the "Insight over Code" philosophy, prioritizing actionable insights that drive business value. If you are looking for a data professional who can enhance your data strategy and deliver comprehensive analytics solutions, let's connect and discuss how I can help optimize your data operations.

I am a Senior Data Analyst with over eight years of experience specializing in Property and Casualty insurance, marketplace, and financial services. I excel in analytics engineering, decision science, and business intelligence, leveraging advanced SQL on Snowflake, dbt transformations, and Python modeling. My expertise includes building robust dimensional models, designing experiments, and managing end-to-end source-to-target migrations. I transform ambiguous business questions into reliable data products that drive strategic decisions for Claims, Underwriting, Finance, Operations, and Distribution teams. With a proven track record of delivering quantifiable business impact and fostering cross-functional collaboration, I am dedicated to mentoring others in the field. If you're seeking a data expert who can unlock insights and support your business goals, I look forward to discussing your project.

I close the gap between "works in demos" and "holds up in production." With 20+ years of engineering experience, I specialize in taking LLM-based systems, RAG pipelines, and data platforms from prototype to production-grade on AWS. I've built clinical AI agents for regulated healthcare environments, production RAG chatbots that reduced analysis time by 30%, and real-time streaming pipelines with 81% latency reduction. I don't just build AI systems — I make them fast, stable, and reliable under real usage. What I bring to your project: deep hands-on experience across the full AI + data stack — RAG pipelines, agentic workflows, MLOps infrastructure, and the AWS data platforms that power them. I think in terms of P95 latency, edge case failure rates, and production reliability, not just demo performance. AI & ML: RAG pipelines · LangChain/LangGraph · LlamaIndex · AI agents · vector search (FAISS, Pinecone, OpenSearch) · LoRA/QLoRA fine-tuning · MLflow · AWS Bedrock · OpenAI · Anthropic · PyTorch · Hugging Face Data Engineering: ETL/ELT · data lakes/lakehouses · Delta Lake · Apache Spark · Databricks · Kafka · Flink · Kinesis · schema modeling · governance Cloud & Infrastructure: AWS (ECS, Lambda, SageMaker, Glue, EMR, Redshift, DynamoDB, S3, Athena, CloudWatch) · Terraform · Docker · Kubernetes · GitHub Actions · Airflow Languages: Python · SQL · Java · PySpark · Bash

I help companies design scalable data architectures and production-ready AI and machine learning systems. With 6+ years of experience across fintech and startups, I build high-performance ETL/ELT pipelines, modern data warehouses, and applied ML/LLM solutions, from classical machine learning models to RAG-based generative AI systems using embeddings and vector databases. What I can help you with: - Designing scalable data pipelines and orchestration workflows - Building Snowflake and modern cloud data warehouses using dbt - Developing classical ML models and LLM-based applications (GPT, RAG, hybrid search) - Creating semantic, vector, and hybrid search systems (Elasticsearch, pgvector) - Optimizing performance, cost, and infrastructure - Ensuring data quality, testing, and governance I focus on building production-grade systems that scale, not experimental prototypes. If you're looking for a technical partner who bridges data engineering, machine learning, and modern AI, let’s talk.

Full Stack & Data Engineering Specialist I'm a versatile Engineer with 5+ years of expertise spanning full stack development, data engineering, and system design. My experience encompasses building enterprise-scale applications, data pipelines, and distributed systems that serve millions of users. Core Technical Expertise: Frontend Development - Expert in React.js, Next.js 14 (App Router), and TypeScript - Proficient with modern UI libraries (shadcn/ui, Material-UI) and TailwindCSS - Specialist in data visualization using D3.js, Three.js, and Chart.js Backend & System Design - Advanced expertise in Python frameworks: FastAPI, Django, Flask - Microservices architecture design handling 50K+ requests/second - Experience with GraphQL, gRPC, and REST API design - Strong knowledge of distributed systems and event-driven architecture Data Engineering & Analytics - Expert in building ETL pipelines using Apache Spark, Airflow, and Kafka - Proficient with data processing using Pandas, NumPy, and PySpark - Experience with real-time streaming analytics and data warehousing - Skilled in ML model deployment and monitoring Database & Infrastructure - Extensive experience with PostgreSQL, MongoDB, Redis, Elasticsearch - Expertise in message queues: Kafka, RabbitMQ, AWS SQS - Proficient with AWS (20+ services), Docker, and Kubernetes - Implementation of caching strategies and performance optimization Notable Achievements: - Reduced system latency by 70% through architecture optimization - Built systems handling 50K+ requests/second with 99.99% uptime - Processed 10TB+ data daily with 80% reduction in processing time - Decreased infrastructure costs by 40% through efficient design - Created reusable component libraries with 100% test coverage - Published multiple technical libraries Recent Project Highlights: Enterprise Solutions 1. Analytics & Data Platform - Processed 1M+ daily events with 5ms response time - Implemented 15+ interactive visualizations - Built real-time data pipelines with Kafka and Spark - Created automated ETL workflows using Airflow 2. Learning Management System - Served 100K+ active users - Implemented automated grading system with ML integration - Reduced API response time by 70% through Redis caching - Processed 50GB+ daily student data 3. Distributed Cache System - Built high-performance caching solution using Redis Cluster - Implemented cache coherency and eviction strategies - Achieved 99.9% availability - Created comprehensive monitoring and backup systems Data Engineering Projects 1. Real-time Processing System - Processed 100K+ events/second using Kafka - Implemented exactly-once delivery - Achieved sub-second latency - Built comprehensive monitoring dashboard 2. Data Warehouse Solution - Implemented using Snowflake and dbt - Created transformation logic and data modeling - Built automated data pipelines - Implemented governance and security controls 3. Feature Store Platform - Built ML feature computation and serving layer - Implemented versioning and monitoring - Created API interface with caching - Added comprehensive access controls Specialized Skills: - System Design & Architecture - Performance Optimization - Data Pipeline Development - Real-time Processing Systems - Machine Learning Operations - Security Implementation - DevOps & CI/CD - Technical Documentation I excel in delivering: - Scalable web applications and distributed systems - High-performance data processing pipelines - Real-time analytics and visualization solutions - Machine learning model deployment systems - Enterprise-grade architectural solutions My comprehensive technical background, attention to detail, and strong communication skills ensure successful project delivery across various domains. I'm available for both complex long-term projects and targeted short-term engagements, particularly those requiring innovative solutions in full stack development, data engineering, or system design.

Computer Science graduate with hands-on experience in data engineering, analytics, backend systems, and AI-related data tasks. Skilled in building reliable and well-structured data solutions using SQL, Snowflake, Python, Azure, Matillion, Airflow, and cloud-based workflows. Experienced in ETL/ELT processes, data modeling, API integrations, troubleshooting, and maintaining scalable data pipelines that support reporting, automation, and business operations. In addition to technical expertise, I am a native Amharic speaker with strong English communication skills and experience supporting AI data annotation, transcription, voice and language evaluation, quality review, and structured data analysis tasks. I am detail-oriented, adaptable, and focused on delivering accurate, practical, and high-quality work. I also have solid web development knowledge using PHP, HTML, CSS, JavaScript, and Bootstrap, allowing me to support both backend and web-related projects effectively.

I build privacy-safe, scalable data pipelines — the kind that let companies use sensitive data without exposing it. Right now, I lead synthetic data generation on a Privacy Enhancing Technologies team, turning regulated datasets into analytics-ready assets on Databricks and Delta Lake. Over the past 4+ years, I've designed and shipped cloud-native ETL pipelines for large multinationals and product companies. My core stack is Databricks, PySpark, Delta Lake, Unity Catalog, and AWS, and I focus on the parts that actually bite in production: high-throughput processing, clean data modeling, and cost/performance optimization. What I can help you with: • Building or fixing Spark/Databricks pipelines that are slow, fragile, or expensive • Synthetic data generation for testing or privacy-sensitive use cases • Designing Delta Lake / Unity Catalog architectures from scratch • Migrating or optimizing existing ETL workflows If you've got a messy data problem and want someone who's solved it before at scale, send me a message — happy to talk through your project and where I can add the most value.

I’m a Data Engineer and Architect with over 17 years of experience building scalable data solutions for global leaders like CEMEX, Heineken, and Metalsa. Whether you need to develop robust data pipelines, integrate complex APIs, or build high-level analytics platforms, I can help. - Expertise in Programming & ETL: * Proficient in Python, C#, C++, and Java for custom data processing and software development. * Advanced orchestration using Azure Data Factory, Fivetran, dbt, and MS Integration Services (SSIS). * Seamless data transportation from SAP HANA, Oracle, and APIs into Snowflake or Azure SQL. - Advanced Visualization & BI: * Full development of interactive dashboards in Power BI, Tableau, QlikView, and Qlik Sense. * Specialized reporting with Crystal Reports and institutional formatting for end-users. - End-to-End Project Management: * Automation of financial balances, manufacturing KPIs, and predictive maintenance forecasting.Bridge the gap between technical architecture and business objectives.

I am a skilled Data Engineer with over 8 years of experience in designing and scaling data platforms and real-time streaming systems. Whether you are trying to migrate your data from one service to another or aiming for POC for priority project with a tight deadline or need help with designing the best architecture considering company's tech ecosystem and fellow colleague's expertise , I am great fit because >> Hands on Python , SQL , AWS, GCP , Spark , Kafka , Snowflake etc >> Built Real time pipelines supporting 10M+ messages/day using Kafka , Flink on AWS ecosystem . >> Architected and Built Data Platform from scratch powering 30+ Data analysts. >> Breaking down vague requirement to high level architecture and delivering it. >> Strong Communicator to business and techies . Lets connect and let me unblock your business from data requirements.