SUMMARY Data Scientist with 12 years of international experience in engineering and data-driven projects within major corporations. Skilled in machine learning, statistical analysis, image and video analysis, and process optimization, with a proven track record of delivering impactful solutions and cost savings

I am a Data Engineer and Analyst with over 3.5 years of experience in creating and optimizing scalable ETL/ELT pipelines using Snowflake and AWS. My expertise encompasses data warehousing, data modeling through Star and Snowflake schemas, and pipeline performance optimization, particularly in the Healthcare/Pharma and Finance sectors. I have successfully reduced query execution time by 40% and achieved a 99.8% pipeline success rate, delivering significant results that drive efficiency and decision-making. Currently pursuing an MBA in Business Analytics and International Business Management, I aim to enhance my data-driven insights and business acumen. If you need a data expert who can transform complex data into actionable insights, I'm ready to collaborate on your project.

I am a Top Rated Plus Upwork freelancer with over 5+ years of extensive Python programming experience. My passion for innovation and programming aligns seamlessly with the demands of modern data engineering. I specialize in building and maintaining data pipelines, data warehouses, and data lakes. I have experience with a variety of Python libraries and frameworks, including NumPy, Pandas, Matplotlib, Seaborn, Apache Spark, and Apache Kafka. I am also proficient in SQL and NoSQL databases, and I have experience with cloud computing platforms such as AWS and Azure. Additionally, I have expertise in web scraping and microservices. Here are some of the data engineering, web scraping, and microservices skills and expertise that I have, along with the tools that I am proficient in: ✅Data pipeline development (Apache Airflow, Apache Spark, dbt) ✅Data warehousing (Amazon Redshift, Snowflake, Google BigQuery) ✅Data analysis (Python, SQL) ✅Data modeling (Star Schema, Snowflake Schema, Fact Table and Dimension Tables) ✅Cloud computing platforms (AWS, Azure, Google Cloud Platform) ✅Big data processing (Apache Spark, Hadoop) ✅Data streaming (Apache Kafka, Amazon Kinesis) ✅NoSQL databases (MongoDB, Elasticsearch) ✅Data visualization (Tableau, Power BI) ✅Microservices (Docker) ✅Web scraping (Selenium, BeautifulSoup, Scrapy) I am always looking for new ways to use technology to solve real-world problems. I am confident that I have the skills and experience to help you with your data engineering, web scraping, and microservices needs. Please contact me today to discuss your project. But the main point: I have a responsibility for the final result.

Data platforms fail for predictable reasons — poor architecture, no testing, brittle pipelines, no CI/CD. I fix that. I specialize in high-throughput data engineering on Microsoft Azure and Microsoft Fabric, with 5+ years building production systems that enterprise teams actually rely on. My core approach is Medallion Architecture (Bronze / Silver / Gold) with Delta Lake, PySpark, and automated deployment from day one. 𝗖𝗼𝗿𝗲 𝗲𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲: 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀 Microsoft Fabric · Azure Synapse Analytics · Databricks · AWS (S3, Glue, Lambda, Athena, CloudWatch) 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 PySpark (OOP) · SQL / T-SQL · Azure Data Factory · Dataflow Gen2 · Apache Airflow · dbt · Delta Lake / Parquet 𝗜𝗻𝗳𝗿𝗮 & 𝗤𝘂𝗮𝗹𝗶𝘁𝘆 CI/CD (Azure DevOps / GitHub Actions) · Docker · Git · pytest / TDD · dbt testing 𝗕𝗜 & 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 Power BI · PostgreSQL · MS SQL Server · OneLake · Fabric Shortcuts I work well with teams who need someone to own the data layer end-to-end — not just write code, but think through design trade-offs, set up proper testing, and make sure the next engineer can maintain what I build. Open to greenfield builds, architecture reviews, pipeline migrations, and ongoing platform work. Let's connect.

5+ YOE Data Engineer and Analyst | Python Developer | MLOps / LLMOps 📌 HOW I CAN HELP YOU: ✅ Build automated ETL/ELT pipelines to save your team hours of manual work. ✅ Build BI platforms with automation tools and dashboarding for repetitive workflows and reporting. ✅ Data Extraction, Mining, Cleaning, Analysis or Modeling. ✅ Delivering clean, structured data (CSV, Excel, JSON, databases) ✅ Migrate your data to Databricks, Snowflake, or BigQuery. ✅ Develop custom AI/LLM infrastructure and MLOps workflows. ✅ Audit and secure your existing data architecture. ✅ Database Design – Relational - PostgreSQL, MySQL, SQLite, NoSQL - MongoDB, Vector - Pinecone, Milvus 📌 WHY CHOSE ME? 🔹 Banking-Grade Integrity: I treat your data with the strict security and confidentiality required by Tier-1 financial institutions. 🔹 Clean, Maintainable, & Scalable Code: I build for the long term, ensuring your systems handle scale and high volume without breaking. 🔹 On-Time Delivery: I respect your timelines and provide regular updates to ensure we stay on track. 🔹 Strong Communication & Proactive Problem-Solving: No jargon—just clear facts, quick iterations, and practical solutions that move the needle for your business. 🚀 📌 ABOUT ME: I’m a Data Engineer and Python Developer with a focus on building secure data pipelines, automating complex workflows, and creating high-performance analytics systems and AI use cases. With a background as an SME for global credit portfolios at Global Tier-1 Bank, I specialize in turning fragmented, high-volume data into clean, actionable infrastructure. ⚙️ I help businesses structure their data landscape, automate repetitive manual processes, and migrate legacy systems into modern cloud environments. My approach is practical and "security-first": I prioritize scalability, data integrity, and solutions that are easy for your team to maintain. My expertise spans the entire data lifecycle -- from Data Engineering and Architecture to Predictive Modeling and MLOps. Whether you are moving legacy data to the cloud or building the infrastructure for a new AI application, I ensure your systems are automated, scalable, and, most importantly, secure. 📌 TECHNICAL TOOLKIT I am proficient across the major cloud ecosystems and specialized data tools: - Cloud Stacks: Azure: Databricks, Synapse, ADF, ADLS, AKS, AzureML - AWS: Glue, Lambda, Redshift, S3, Athena, SageMaker, EC2 - GCP: BigQuery, Looker, Pub/Sub, Dataproc - Engineering & Big Data: PySpark, Spark, Hive, Kafka, Hadoop, Airflow, Sqoop - Databases: Postgres, MongoDB, DynamoDB, Redis, Pinecone (Vector), DB2 - Programming: Python (Expert), SQL, Scala, Shell/Unix, SAS, R, C++ - AI/MLOps: Scikit-learn, PyTorch, TensorFlow, LLM Infrastructure, Docker, Kubernetes - Mainframe Modernization: COBOL, JCL, DB2, TSYS TS2®, z/OS - BI & Analytics: Tableau, Power BI, Looker, Alteryx, GA4 📌 EXPERIENCE BY INDUSTRY - Banking & Finance (SME) | E-commerce | Retail | Automotive | IT Services - Methodologies: SAFe® Agile, Scrum, Kanban, DevOps (CI/CD) Ready to streamline your data? Let’s hop on a quick call to discuss your project!

Data Engineer | AWS | Artificial Intelligence Analyst/Data Engineer, with more than 10 years of experience in the Analytics area. Recognized for its strengths in data analysis, understanding of business dynamics, ETL, Data Warehouse, database programming and statistical tools, code reengineering, working with solutions for the full cycle of the data modeling process and leveraging analytics to extract information and provide insights. CERTIFICATIONS - SQL SERVER ADM - AWS Cloud Pratictioner Cloud Computing # AWS (S3, EC2, Lambda, Event Bridge, AWS Step Functions, Api gateway +20 Amazon Services) Databases # Oracle # SQL Server # MySQL # Mysql # Teradata # Data Stage # Mongo DB Unified Data Analytics Plataform # Cloudera (CDP) # Databricks ( boost Spark inside in a cloud-based managed plataform ) # Hadoop Ecosystem (HDFS, Sqoop, Hive, Hue, Impala) # Apache Spark (RDD, Streaming, Scala, PySpark) # Apache Hive Expert (DW & ETL) Language # SQL # Python # .Net | C# # Java # Shell Script ETL # Integration Services # Apache Sqoop (Data Ingesting) Others # Linux # Machine Learning libraries # Jupyter Notebook # Google Colab Most Recently Experience - I play with Hadoop framework projects recent 4 years; - Participating in Big Data projects with Sqoop, Hive, MapReduce, storage in HDFS / S3. - Developing a Platform Data Processing on AWS Services using python and .NET; - Nowadays I'm focusing in studying to certify in AWS Developer Certification - Experience on the sectors: Mining, Bank & Pharmaceutical - Outstanding skill on (hands-on) Oracle DB(PL/SQL), MS-SQL Server, Big Data Platform and Python

I’m a Data / AI Engineer specializing in Databricks-based data platforms and production-grade AI solutions. I help businesses turn data into practical outcomes by building scalable lakehouse architectures, reliable ETL pipelines, and intelligent AI workflows that are ready for real-world use. My background includes designing unified data and AI platforms on Databricks, developing MLflow-based model tracking and serving workflows, and building agentic applications with LangChain, LangGraph, and MCP servers. I’ve delivered GenAI solutions for enterprise use cases such as knowledge retrieval, customer support automation, and claims processing, with a strong focus on guardrails, traceability, and business impact. What I bring: - Databricks lakehouse and data engineering. - AI agent development using LangChain, LangGraph, and MCP. - MLflow, model serving, and MLOps. - RAG pipelines and enterprise GenAI solutions. - Python, SQL, PySpark, Azure, AWS, and CI/CD automation. I’m especially comfortable working on projects that require both solid data engineering foundations and practical AI delivery, from backend pipelines to production-ready intelligent systems. If you need someone who can bridge Databricks, MLOps, and agentic AI development, I can help design and build it end-to-end.

I am a Data Analyst and Analytics Engineer with a strong foundation in chemical engineering and two years of hands-on experience in designing and deploying production-scale data systems. I specialize in transforming complex datasets into actionable insights using Python, SQL, dbt, Power BI, and LangChain. My expertise lies in the BFSI, ESG, Legal Tech, and Insurance sectors, where I have successfully completed four end-to-end projects involving over a million records with 99.9% accuracy. These efforts have led to operational efficiencies of up to 80% and enhanced revenue forecasting by 30%. If you need a skilled data professional who can unlock the full potential of your data and drive impactful business decisions, I'd love to discuss how I can contribute to your success.

I help companies build reliable, scalable data infrastructure — from raw ingestion to analytics-ready pipelines and AI-powered workflows. 🔧 What I specialize in: - Data Architecture: Data Warehouse, Data Lake, Lakehouse & Medallion Architecture design - Cloud Platforms: AWS, GCP, Azure (multi-cloud experience) - Pipeline Orchestration: Apache Airflow, Kestra, n8n - Data Transformation: dbt, Apache Spark - Storage & Compute: Snowflake, BigQuery, Redshift, Databricks - BI & Analytics: Power BI, Looker, Tableau, QuickSight - AI Integration: LangChain, TensorFlow, Keras — building AI-ready data layers and RAG pipelines - Languages: Python, Advanced SQL 🏗️ I don't just build pipelines — I design the architecture behind them. Whether you need to migrate to the cloud, modernize a legacy warehouse, implement a Medallion Architecture, or integrate LLMs into your data stack, I deliver solutions that scale with your business. ✅ Clean documentation ✅ On-time delivery ✅ Clear communication throughout the project Let's discuss your data challenges.

PROFILE Dynamic Senior Data & Analytics Engineer with over eight years of robust experience in designing and optimizing data solutions that drive business insights and operational efficiency. Proficient in leveraging advanced modern stack technologies such as AWS, Databricks and Snowflake to create scalable data pipelines and effective data models. Strong expertise in data visualization tools and methodologies ensures impactful reporting and decision-making support for stakeholders. A proven track record of collaborating with cross-functional teams to align data strategies with business objectives, fostering an environment of continuous improvement and innovation.