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🚀 I help startups and enterprises build scalable, production-ready software with a strong focus on Java, Spring Boot, and modern backend architecture. As a Software Engineer, I have designed and delivered systems ranging from start-up MVPs to enterprise and government platforms serving thousands of daily users. My expertise is cantered around building clean, maintainable, and high-performance backend applications, while also collaborating across the full software stack whenever projects require it. What I can help you build: ✔ Java & Spring Boot Applications ✔ REST APIs & Backend Services ✔ Microservices Architecture ✔ Authentication & Security (JWT, OAuth2, Keycloak) ✔ Event-Driven Systems (Kafka, RabbitMQ) ✔ Database Design & Optimization ✔ Performance Optimization ✔ System Integration ✔ Cloud-ready Applications ✔ Software Architecture & Code Refactoring Technologies I work with include Java, Spring Boot, Spring Security, Hibernate, PostgreSQL, MySQL, MongoDB, Redis, Kafka, RabbitMQ, Docker, Camunda, Keycloak, AWS, and modern observability tools. Beyond my primary backend expertise, I have also delivered successful projects using Python, FastAPI, Django, React, Next.js, Flutter, and Supabase whenever they were the right technology for the job. 🌟 Highlights • Architected and developed the complete backend microservices platform for "Crewpr", a Dubai-based startup, designing 10+ microservices, integrating multiple third-party services, and building a scalable production system serving thousands of active users. • Contributed to digital transformation projects for Irish government organizations, including Enterprise Ireland, NEH, and Startup Ireland, building secure and scalable backend systems. • Improved the performance and scalability of Yugo, a large-scale European student accommodation platform, by developing backend features and integrating external hospitality systems including RentCafe, Student Suite, and Entrata.

It was the most important moment of my 13+ years of career. It was when I realized that there is always a trade-off in technology. You have to do something intentionally bad in order to succeed as a Small Medium Business in the Digital Transformation. And 70% fail because they insist on doing this very thing well. A while back, when I finally landed a job in a corporation, I was excited that I was going to use state-of-art technology. But, one of my first features immediately added some bugs. As I fixed those bugs, I introduced another, but also other bugs started to pop up caused by previous developers. In laymen terms, it is like a Rubik’s cube. As you carry on assembling the second face, you may accidentally mess up the first bit. It wasn’t like that when I started my career in technology in the civil service a long time ago. Yes, I was frustrated because we used old boring technology. But, we didn’t have to put out the fire all the time because that limited technology prevented us from getting in this position. Coincidence or not, the easiest way to solve the Rubik’s cube is putting constraints. If you move towards, you have to move backwards at some point. Fast forward to nowadays, some of my clients want to create highly customized User Experience. As the project starts to grow, hyper customization introduces more complexity. Then, you make a small change and get unexpected results. You didn't account for all the complex consequences. And this happens again and again, and you can’t avoid it. The software had become brittle. You start to miss deadlines or have to hire more developers to fix cracks faster, and eventually I get hired. That’s the time I have the hard talk: don’t bite more than you can chew, stop chasing the perfect User Experience (good User Interface is not a problem though) with a small team. If a BigTech didn’t have to hire thousands of engineers to provide that, they certainly wouldn’t. Anyway, User Experience is only noticed by B2C clients, and this is where Big Techs thrive. In B2B or internal tool software, who pays for the software won’t even use it. Hey, my name is João, I’m a software architect and developer, feel free to send me a message asking how I can make your business grow. What technologies do I work with? The simple ones: HTML, CSS, Bootstrap, Bash, XML, PostgreSQL, Apache Camel, Apache Knowledge Is Everything, Keycloak. If you need a hypercustomized solution, I can decently program in Java, Python and JavaScript, though. If you have any doubts, don’t hesitate to contact me.

I build data platforms that work at scale and keep working as your business grows. Over the past 10 years I've served as the lead or founding data engineer across fintech, e-commerce, ride-hail, legal tech, and cybersecurity companies. That means I've designed systems from scratch, made architecture decisions with no one to fall back on, and delivered platforms that product teams actually use. Here's what I typically get hired to do: → Build greenfield data platforms on AWS or GCP from the ground up → Design and ship production ETL/ELT pipelines (Airflow, Dagster, dbt) → Set up scalable warehouses and governance (Snowflake, BigQuery, Redshift) → Implement real-time streaming pipelines (Kafka, Spark Streaming, CDC) → Build AI-powered data applications (RAG, LLMs, LangChain, vector DBs) → Fix broken or unreliable pipelines and make them production-grade → Architect cloud infrastructure on AWS, GCP, Azure (Terraform, Kubernetes) Recent work includes: - Led data platform engineering for a US e-commerce company processing billions of events daily. I re-architected ingestion pipelines, built Snowflake governance from scratch, introduced Prometheus monitoring and CI/CD standards across the platform. - Built a full data platform on GCP (BigQuery, Dataproc, Airflow) for a music streaming company. Firebase, AppsFlyer, and app store data all flowing into one warehouse within weeks. - Designed an AWS data platform for a ride-hail company managing 500+ streaming and 700+ batch jobs — including a self-serve portal that replaced multi-step CLI workflows for engineers. - Built a legal AI search engine using LangChain, Pinecone, and RAG — full pipeline from document ingestion to LLM-generated answers, deployed on AWS with auto-scaling. - Built an AI inventory insights agent for a US automotive company — multi-source data pipelines, real-time APIs, conversational interface. I work in English daily, communicate proactively, and deliver production- ready code — not prototypes. I'm used to working directly with CTOs and technical leads in US and European time zones. Tools I work with regularly: Python · SQL · Airflow · Dagster · dbt · Snowflake · BigQuery · Spark · Meltano · Kafka · AWS (S3, EMR, Glue, ECS, Lambda, EC2, EKS) · Databricks · GCP · Azure Terraform · Docker · Kubernetes · LangChain · FastAPI · MLflow · Weaviate, Celery If you're building a data platform, fixing one, or adding AI/ML capabilities to your stack, let's talk.

Struggling to unlock value from your data or build scalable, high-performance analytics platforms? I’m 𝑯𝒂𝒔𝒆𝒆𝒃 𝑨𝒔𝒊𝒇,a Senior Data Engineer specializing in Databricks, Snowflake, Big Data Engineering, and scalable ETL/ELT solutions. With expertise in PySpark, Python, SQL, GCP, AWS, Azure, and NLP, I build high-performance data pipelines, cloud data platforms, and real-time analytics solutions. Experienced in data warehousing, cloud integration, machine learning workflows, and performance optimization to transform raw data into actionable business insights. Let’s build reliable, scalable, and data-driven solutions for your business growth. I’ve successfully completed 99+ projects across industries, designing ETL pipelines, MLOps workflows, Delta Lake architectures, and cloud analytics solutions on AWS, Azure, and GCP. ✔️ 𝑯𝒐𝒘 𝑰 𝑯𝒆𝒍𝒑 𝑩𝒖𝒔𝒊𝒏𝒆𝒔𝒔𝒆𝒔 𝑻𝒓𝒂𝒏𝒔𝒇𝒐𝒓𝒎 𝑫𝒂𝒕𝒂 𝒊𝒏𝒕𝒐 𝑰𝒏𝒔𝒊𝒈𝒉𝒕𝒔 ➜ Databricks & Big Data Engineering I specialize in designing enterprise-grade Databricks Lakehouse architectures and Delta Lake solutions. My expertise in Spark and PySpark allows me to build high-performance pipelines for both batch and real-time analytics, ensuring your data infrastructure is robust and scalable. ➜ Machine Learning & MLOps With a focus on machine learning and MLOps, I build and deploy predictive models using tools like MLflow and TensorFlow. I automate end-to-end ML pipelines to enhance efficiency and accuracy, driving impactful insights from your data. ➜ Cloud & Data Platforms I implement secure, scalable cloud solutions on platforms like AWS, Azure, and GCP. My experience includes cloud migration, Kubernetes, Docker, and CI/CD automation, ensuring seamless integration and optimal performance. ➜ ETL & Data Pipelines I develop reliable ETL processes and data pipelines that streamline data integration and transformation. My work with streaming analytics using Kafka and Spark ensures real-time data processing and actionable insights. ➜ Data Analyst & Visualization I create actionable dashboards and visualizations using Power BI, Tableau, and Databricks SQL. My focus is on driving KPI reporting and business intelligence to support strategic decision-making. ➜ Snowflake I leverage Snowflake's capabilities to build efficient data warehousing solutions, optimizing data storage and retrieval for enhanced performance and scalability. ➜ Python My proficiency in Python allows me to develop complex data processing scripts and machine learning models, ensuring robust and efficient data handling. ➜ NLP (Natural Language Processing) I apply NLP techniques to extract meaningful insights from unstructured data, enabling advanced text analytics and improved decision-making processes. ➜ GCP (Google Cloud Platform) I utilize GCP's powerful tools to design and deploy scalable cloud solutions, ensuring high availability and performance for your data-driven applications. ➜ Data Warehouses I design and manage data warehouses that provide a centralized repository for your data, facilitating efficient data analysis and reporting. ✔️ 𝑲𝒆𝒚 𝑻𝒐𝒐𝒍𝒔 & 𝑻𝒆𝒄𝒉𝒏𝒐𝒍𝒐𝒈𝒊𝒆𝒔 ▪ Databricks & Big Data: Databricks, Delta Lake, Apache Spark, PySpark, Unity Catalog, Kafka, Hadoop, Real-time Streaming ▪ Machine Learning: MLflow, TensorFlow, PyTorch, scikit-learn, Feature Store, Predictive Analytics, NLP ▪ Cloud Platforms: AWS, Azure, GCP, Kubernetes, Docker, CI/CD ▪ Analytics & BI: Power BI, Tableau, Databricks SQL, KPI Dashboards, Data Strategy ▪ Data Engineering: ETL Pipelines, Data Lakes, Data Warehousing, Data Migration, Performance Optimization ✔️ 𝑾𝒉𝒚 𝑪𝒉𝒐𝒐𝒔𝒆 𝑴𝒆 I combine deep technical expertise with practical business understanding, delivering scalable, cost-efficient, and AI-ready data solutions. My goal is to turn your data into a strategic asset that powers smarter decisions and measurable growth. Let’s collaborate to build your next-generation analytics platform and unlock the full potential of your data. Check my portfolio for architecture samples, dashboards, and case studies. Databricks Engineer, Big Data Consultant, Spark Developer, MLOps Engineer, Data Engineer, AWS Data Specialist, Azure Databricks, GCP Analytics, ETL Developer, Data Analytics, Delta Lake Expert, Machine Learning Engineer, Python, Database Architecture, Data Processing, ETL, Big Data, Database Design, Data Engineering, Data Analytics & Visualization Software, Data Visualization, Deep Learning Modeling, Data Warehousing & ETL Software, Snowflake, Amazon Web Services, ETL Pipeline, Machine Learning, Deep Learning, Data Science, Data Analysis, Cloud Engineering, Artificial Intelligence, Databricks Engineer, Big Data Consultant, Spark Developer, MLOps Engineer, Data Engineer, AWS Data Specialist, Senior Data Engineer specializing in Databricks, Snowflake, Big Data Engineering, and scalable ETL/ELT solutions. With expertise in PySpark, Python, SQL, GCP, AWS, Azure, and NLP

I’m a Full Stack Developer & Technical Team Lead with over 15 years of experience delivering reliable, scalable, and secure web solutions. I specialize in ColdFusion (including Lucee), Amazon SP API, and PHP frameworks like Laravel, WordPress, and CodeIgniter, helping businesses modernize legacy systems and build high-performing applications. 💼 Core Expertise Backend & APIs: ColdFusion, Lucee, PHP (Laravel, WordPress, CodeIgniter), RESTful APIs, Amazon SP API, payment gateways, CRM integrations. Frontend & UI: HTML5, CSS3, JavaScript, React, Vue.js, Bootstrap, Tailwind CSS — responsive, modern, and user-friendly designs. Cloud & Deployment: AWS, DigitalOcean, cPanel/WHM, CI/CD pipelines, server optimization. Database Management: MySQL, PostgreSQL — optimized for scalability and performance. 🚀 Why Clients Hire Me I combine legacy system expertise with modern full-stack development, ensuring seamless ColdFusion/Lucee modernization, API integration, and PHP application development. I deliver projects that are secure, maintainable, and on schedule, with clear communication and a focus on business outcomes. 💡 My goal is to transform your ideas into high-performing, reliable digital solutions that drive growth and inspire confidence in your customers.

I'm a Senior Data Engineer with 8+ years of strong technical expertise in building reliable and scalable data infrastructure, from data ingestion to transformation to warehousing, streaming, and data analytics, specializing in dbt, Snowflake, Airflow, Databricks (and more) across AWS, Azure, and GCP, with robust ELT and ETL pipelines. If your data pipelines are brittle, your data warehouse is slow, or your data was never built to scale, that is exactly what I fix, with fault tolerance, observability, and audit-ready quality engineered in from day one. I cover the full data engineering lifecycle: batch and real-time data pipelines, Modern Data Stack builds, lakehouse architecture, cloud and warehouse data migration, governance, and the data foundations that feed modern systems. 🎯 Core Expertise: ✅ Data Pipelines & Orchestration: End-to-end batch and real-time pipelines with Apache Airflow, Dagster, Prefect, AWS Step Functions, and Azure Data Factory. Idempotent, schema-drift tolerant, and monitored so failures surface before they reach your stakeholders. ✅ Cloud Warehousing & Lakehouse: Snowflake, BigQuery, Amazon Redshift, Databricks, and Microsoft Fabric, with Delta Lake and Apache Iceberg lakehouse foundations governed through the Glue Data Catalog and Lake Formation, with Athena and Redshift Spectrum for serverless queries, Medallion Architecture, partitioning, and performance tuning. ✅ Data Transformation & Modeling: dbt (Core and Cloud), SQLMesh, Spark and PySpark on EMR and AWS Glue, Star Schema and dimensional modeling, analytics engineering best practices, full test coverage, and CI/CD for data models. ✅ Streaming & Real-Time Analytics: Distributed streaming with Apache Kafka, Flink, Spark Structured Streaming, Kinesis, and Pub/Sub, including exactly-once semantics, dead-letter queues, CDC, and end-to-end latency guarantees. ✅ Data Ingestion & Integration: Fivetran, Airbyte, Matillion, Stitch, Hevo, Meltano, and custom CDC pipelines for near-real-time sync across structured, semi-structured, and unstructured sources. ✅ Data Quality, Governance & Observability: Automated data quality frameworks, SLA monitoring, auditable lineage, data catalog and metadata management, and observability that catches bad data early. ✅ Cloud Migration & Modernization: Zero-downtime migration handled end to end, from legacy warehouse assessment through cutover, with zero data loss and minimal downtime, replacing brittle ETL and ELT with a clean Modern Data Stack. ✅ AI-Ready Data Infrastructure: Pipelines engineered to feed LLMs and ML systems with clean, structured, high-quality data, from ingestion through transformation to serving. ------------------------------------------------------ ⚙️Tech Stack: ⚡ Warehouses & Lakehouse: Snowflake | BigQuery | Redshift | Databricks | Microsoft Fabric | Athena | Delta Lake | Iceberg ⚡ Transformation: dbt | SQLMesh | Spark | PySpark | AWS Glue | EMR | Star Schema | Medallion Architecture ⚡ Orchestration: Airflow (GCP Cloud Composer and AWS MWAA) | Dagster | Prefect | Azure Data Factory | Step Functions ⚡ Streaming: Kafka | Flink | Kinesis | Pub/Sub | Spark Structured Streaming | ClickHouse ⚡ Ingestion: Fivetran | Airbyte | Matillion | Stitch | Hevo | Meltano | CDC ⚡ Governance & Catalog: Glue Data Catalog | Lake Formation | Unity Catalog | Microsoft Purview | Dataplex ⚡ Cloud: AWS | GCP | Azure ⚡ Languages: Python | SQL (Snowflake, BigQuery, T-SQL, PL/pgSQL) | FastAPI ⚡ Databases: PostgreSQL | MySQL | SQL Server | DynamoDB | MongoDB ⚡ BI & Reporting: Looker | Tableau | Power BI | GA4 | Metabase | Superset | Streamlit | Grafana ------------------------------------------------------ ⭐ What Clients Say: 🏅 "Adarsh rebuilt our analytics pipeline on Snowflake, Airflow, and dbt, giving us reliable, version-ready data. Reporting accuracy improved overnight, and we can finally trust the numbers." – Anita, Head of Product, FinTech SaaS 🏅 "He designed a zero-downtime migration to a modern data warehouse that cut query latency by more than half while keeping our SLAs intact." – Daniel, VP of Data, AdTech Firm 🏅 "Clean architecture, solid dbt models, and Airflow pipelines running without issues for months. He brought a level of engineering discipline we hadn't seen from a data consultant before." – Mark, Director of Data Engineering, E-commerce Startup 🏅 "We came to him with a Spark pipeline costing us a fortune and delivering stale data. He restructured the workflow logic and cut processing time by 70%." – Leo, Head of Analytics, HealthTech SaaS ------------------------------------------------------ 🏆 TOP RATED PLUS | EXPERT-VETTED | Top 1% on Upwork | 8+ Years Experience | 100% Job Success 🚀 Ready to build a scalable, production-ready data infrastructure to turn your raw data into reliable, actionable business insights? Click the 'Invite to Job' button on the top right, and let's discuss your data pipeline!