Hire the Best Big Data Engineers

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.

𝐈 𝐛𝐮𝐢𝐥𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐠𝐫𝐚𝐝𝐞 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 𝐟𝐨𝐫 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐝𝐞𝐚𝐥𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐛𝐫𝐨𝐤𝐞𝐧 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, 𝐬𝐜𝐚𝐭𝐭𝐞𝐫𝐞𝐝 𝐬𝐲𝐬𝐭𝐞𝐦𝐬, 𝐬𝐥𝐨𝐰 𝐫𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐮𝐧𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞 𝐦𝐞𝐭𝐫𝐢𝐜𝐬. I’m a Senior Data Engineer with 10+ years of experience building cloud data platforms, ETL/ELT pipelines, lakehouses, warehouses, and analytics-ready data layers using Microsoft Fabric, Snowflake, AWS, BigQuery, dbt, Python, SQL, Airflow, Fivetran, Airbyte, and Databricks. My focus is not just moving data from point A to point B. I design reliable data systems that are automated, scalable, well-modeled, and trusted by business teams. 𝐖𝐡𝐚𝐭 𝐈 𝐡𝐞𝐥𝐩 𝐰𝐢𝐭𝐡 ✅ 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐚𝐛𝐫𝐢𝐜 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Lakehouse, Warehouse, Dataflows Gen2, pipelines, notebooks, semantic models, Medallion architecture, and Power BI-ready data layers. ✅ 𝐂𝐥𝐨𝐮𝐝 𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, SQL Server, and Azure Synapse architecture. ✅ 𝐄𝐓𝐋/𝐄𝐋𝐓 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 API ingestion, database replication, SaaS integrations, file ingestion, batch jobs, incremental loads, and scheduled workflows. ✅ 𝐝𝐛𝐭 & 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Staging, intermediate, marts, incremental models, tests, documentation, metric definitions, and business logic standardization. ✅ 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 & 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 Airflow, Dagster, AWS Lambda, Glue, Step Functions, ADF, CI/CD, monitoring, retries, alerts, and production workflow automation. ✅ 𝐃𝐚𝐭𝐚 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 & 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 Deduplication, reconciliation, schema drift handling, validation rules, MDM, Golden Record logic, RBAC, access control, and audit-ready reporting layers. 𝐑𝐞𝐜𝐞𝐧𝐭 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐚𝐛𝐫𝐢𝐜 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 Built a centralized Fabric platform with Lakehouse, Warehouse, Dataflows, pipelines, semantic models, and Power BI reporting layers for a global organization with fragmented reporting sources. 𝐍𝐞𝐚𝐫 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 Designed operational pipelines into Snowflake with incremental ingestion, schema change handling, deduplication, retries, and reliable dbt-based reporting models. 𝐌𝐨𝐝𝐞𝐫𝐧 𝐒𝐚𝐚𝐒 𝐝𝐚𝐭𝐚 𝐬𝐭𝐚𝐜𝐤 Centralized HubSpot, Stripe, GA4, Google Ads, Salesforce, MongoDB, and product data into BigQuery/Snowflake using Fivetran, Airbyte, dbt, Dagster, and Metabase. 𝐋𝐞𝐠𝐚𝐜𝐲 𝐦𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐭𝐨 𝐜𝐥𝐨𝐮𝐝 𝐰𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 Led migrations from SQL Server, SAP BW, Oracle, Hadoop, and on-prem systems into modern cloud warehouses with optimized performance and automated workflows. 𝐀𝐖𝐒 𝐝𝐚𝐭𝐚 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 Built automated workflows using S3, Lambda, Glue, Step Functions, IAM, SNS, CloudWatch, and Python to reduce manual reporting and improve pipeline reliability. 𝐓𝐨𝐨𝐥𝐬 𝐈 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 Microsoft Fabric, Snowflake, BigQuery, Redshift, Databricks, Azure Synapse, PostgreSQL, SQL Server, Oracle, SAP BW, Hadoop, dbt, Python, SQL, Airflow, Dagster, Fivetran, Airbyte, ADF, SSIS, Talend, AWS S3, Lambda, Glue, Step Functions, IAM, SNS, CloudWatch, Power BI, Tableau, Metabase, and Looker. You should reach out if you need a senior data engineer to: ✅ Build a cloud data warehouse or lakehouse ✅ Migrate legacy systems to Snowflake, Fabric, BigQuery, or AWS ✅ Fix unreliable ETL/ELT pipelines ✅ Design dbt models and trusted reporting layers ✅ Automate manual reporting workflows ✅ Integrate APIs, CRMs, ERPs, databases, and SaaS platforms ✅ Build production-ready data infrastructure for analytics and BI If your data stack is messy, slow, or hard to trust, send me a message. I’ll help you map the cleanest path from scattered systems to a reliable data platform.

☑️ 14+ Years Professional Experience ☑️ US Client Specialty ☑️ <10 Minute Client Message Response Times ☑️ Outstanding Pro-Active Communication ☑️ 4,600+ Hours Delivered, Maintaining a 100% Job Success Score ☑️ Extensive Experience In: Software - SaaS - eCommerce - Finance ☑️ Worked with Netskope & RSAC ☑️ On Time Every Time ☑️ Long-Term Partnership Mindset 📞 𝗜𝗻𝘃𝗶𝘁𝗲 𝗺𝗲 𝘁𝗼 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗼𝗻 𝗨𝗽𝘄𝗼𝗿𝗸 𝗼𝗿 𝘀𝗲𝗻𝗱 𝗺𝗲 𝗮 𝗱𝗶𝗿𝗲𝗰𝘁 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 𝘁𝗼 𝗯𝗼𝗼𝗸 𝗮 𝗰𝗼𝗺𝗽𝗹𝗶𝗺𝗲𝗻𝘁𝗮𝗿𝘆 𝗰𝗼𝗻𝘀𝘂𝗹𝘁𝗮𝘁𝗶𝗼𝗻 𝗰𝗮𝗹𝗹 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿. ❝ Michael and the DSC team is absolute gold! I cannot speak highly enough of their data insights and software development capabilities, which based on my experience, are second to none! I have served as a product strategy and development leader for a number of major brands, including Starbucks, Microsoft, Wells Fargo and more. Furthermore, I have worked with many talented Power BI, data analytics and software development colleagues, consultants and third party providers. I have never found a more capable team to deliver best-in-class solutions for any data related initiative - simple or complex. ❞ 🗣 Bryan Guy - CEO - Databillity — Hi! I’m Michael. I specialize in supporting US-based clients with exceptional data engineering, data architecture and advanced analytics solutions. I’m the leader of a team of 10 hand-picked Canadian data scientists and data engineers. When you work with me, you work with an industry-leading team of native-English experts. Together, we create outcomes impossible to do individually. The main outcomes I consistently create with my clients are enabling them to make higher-quality business decisions with reliable data, all while reducing manual work and leveraging automation for their entire team. I offer end-to-end solutions. I take responsibility for every step of your data journey. This includes building automated data pipelines that pull information directly from systems like your CRM, ERP, and financial platforms. Your data can then be centralized in a cloud-based data warehouse, creating a single reliable source of data serving as a stable foundation for analysis and reporting. From there, we can work together to determine what matters for your business to track with earnestly helpful reporting dashboards. Your KPI’s and the data you need to make meaningful decisions are communicated clearly in accessible reporting that you and your team will actually use. — One example of a recent successful data engineering project was: Data ingestion and analytics with an American IT security company. Ingesting data from Salesforce (Opps, Leads, Contacts, Campaigns etc.) into Snowflake using Fivetran. Building a metadata layer in Looker using LookML code, and creating dashboards to track key metrics such as ARR and MRR. Overseeing the rollout of dbt, a data transformation platform, used as an intermediary data transformation step between Snowflake and Looker. — Data sources I often work with include: 🔷 CRM & Sales Systems - Salesforce - HubSpot - Proprietary CRM Systems 🔷 Marketing & Analytics Platforms - Google Analytics - Google Tag Manager - Facebook Ads - Marketing Attribution Platforms 🔷 Financial & Payment Systems - Stripe - QuickBooks - ERP Systems - Financial Reporting Tools 🔷 Product & Application Data - Web Apps - Internal Databases - Event Tracking Systems - Custom Application Data 🔷 Cloud & Data Infrastructure - Google BigQuery - Snowflake - Azure-Hosted Data Environments 🔷 Custom & API Integrations - REST APIs - Webhook-Based Systems - Custom Data Pipelines From Internal Tools — Data architect and data engineering services I commonly support my clients with includes: 🔸 Specialties: Snowflake - dbt - Microsoft Power BI - Tableau - Looker Studio 🔸 Data Modeling - Data Architecture - Data Engineering 🔸 Reporting - Custom Dashboards - Data Visualization 🔸 Data Warehouse Projects - Data Migrations - Data Transformation - Data Ingestion 🔸 Business Intelligence Projects 🔸 Microsoft Azure - Azure Hosted Data - Azure Hosted Analytics 🔸 Data Engineering Projects 🔸 Automated Testing 🔸 Fivetran - Data Integration Platform Projects 🔸 Airbyte Data Monitoring Tool - Custom Connections Built With: QuickBooks - Microsoft Dynamics - Leadspedia - Everflow - Proprietary CRM systems 🔸 Custom Python Scripts - Custom SQL 🔸 LookML - Amazon Quicksight - Holistics BI - Lightdash - Google BigQuery - Sigma Computing 📞 𝗜𝗻𝘃𝗶𝘁𝗲 𝗺𝗲 𝘁𝗼 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗼𝗻 𝗨𝗽𝘄𝗼𝗿𝗸 𝗼𝗿 𝘀𝗲𝗻𝗱 𝗺𝗲 𝗮 𝗱𝗶𝗿𝗲𝗰𝘁 𝗺𝗲𝘀𝘀𝗮𝗴𝗲 𝘁𝗼 𝗯𝗼𝗼𝗸 𝗮 𝗰𝗼𝗺𝗽𝗹𝗶𝗺𝗲𝗻𝘁𝗮𝗿𝘆 𝗰𝗼𝗻𝘀𝘂𝗹𝘁𝗮𝘁𝗶𝗼𝗻 𝗰𝗮𝗹𝗹 𝘁𝗼𝗴𝗲𝘁𝗵𝗲𝗿. Thank you for learning about how I can support you with your data architect and data engineering project. Michael Nandlall

Most data engineers can write code and connect APIs. But building a data architecture that actually drives business decisions requires understanding the human behavior behind the numbers. With over 14 years of cross-functional experience, I specialize in designing scalable data pipelines and dashboards that turn raw, messy data into clear, actionable business insights. My background is atypical but highly effective: I combine the technical rigor of an Electronic Engineer, the strategic vision of an MBA, and the behavioral insights of a Psychology degree (currently in my final year). This unique mix allows me to go beyond just moving data from point A to point B. I understand the business logic, the financial metrics, and the user behavior you are trying to measure. 🔥 Core Expertise & Tech Stack: Data Engineering & Architecture: Google Cloud Platform (GCP), BigQuery, SQL, Python. ETL/ELT Pipelines: Fivetran, Airbyte, Weld, custom API integrations. Data Transformation: dbt, Dataform. Data Visualization & BI: Looker Studio, Google Sheets, Pandas/Plotly. 📈 Professional Journey Highlights: My experience ranges from acting as a Chief Data Officer (CDO) for software companies to managing complex international operations (including 3 years based in Shanghai, China). I have a proven track record of optimizing architectures, automating workflows, and building data cultures from the ground up. Whether you need to set up a robust data warehouse from scratch, fix broken ETL pipelines, or design dashboards that your stakeholders will actually use, I can help. Let’s connect and discuss how we can build a data architecture that truly serves your business goals.

I'm an 🥇Expert-Vetted, 𝐒𝐞𝐧𝐢𝐨𝐫 𝐀𝐈/𝐌𝐋 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐭𝐢𝐬𝐭 with 𝟏𝟎+ 𝐲𝐞𝐚𝐫𝐬 𝐨𝐟 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 shipping machine learning systems at Fortune 10 companies including Optum, Target, General Mills, and Medtronic. I hold a Ph.D. in Biomedical Engineering and an M.S. in Computer Science (4.0 GPA), combining deep research expertise with real-world engineering skills. My specialty is turning complex AI/ML challenges into deployed solutions that drive measurable business results—especially in healthcare, finance, education, and e-commerce. Right now, I lead AI initiatives that process millions of medical claims. ⚡ 𝐖𝐇𝐀𝐓 𝐈 𝐁𝐔𝐈𝐋𝐃 - 𝐋𝐋𝐌 & 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬 • RAG-based chatbots and Q&A systems using OpenAI, LangChain, and vector databases • Custom LLM pipelines for document processing, summarization, and extraction • Foundation models and domain-specific embeddings using Transformer architectures • Prompt engineering and LLM fine-tuning for specialized use cases - 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 • End-to-end ML pipelines: data processing → model training → deployment → monitoring • Deep learning models (CNNs, RNNs, Transformers) for classification, prediction, and generation • Gradient boosting models (XGBoost, CatBoost, LightGBM) for tabular data • Time-series forecasting, anomaly detection, and predictive analytics - 𝐍𝐋𝐏 & 𝐓𝐞𝐱𝐭 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 • Text classification, named entity recognition, and sentiment analysis • Semantic search and document similarity systems • Neural text embeddings for downstream ML applications - 𝐑𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝𝐞𝐫 𝐒𝐲𝐬𝐭𝐞𝐦𝐬 & 𝐏𝐞𝐫𝐬𝐨𝐧𝐚𝐥𝐢𝐳𝐚𝐭𝐢𝐨𝐧 • Collaborative filtering and content-based recommendations • Neural embedding approaches (item2vec, hierarchical embeddings) • Personalization engines for e-commerce, content, and promotions 🛠️ 𝐓𝐄𝐂𝐇𝐍𝐈𝐂𝐀𝐋 𝐒𝐓𝐀𝐂𝐊 • Languages: Python, SQL, R, C++, Bash • LLM/GenAI: OpenAI API, LangChain, Hugging Face Transformers, RAG • ML/DL: PyTorch, TensorFlow, Keras, Scikit-learn, XGBoost, CatBoost • NLP: spaCy, NLTK, Gensim, sentence-transformers • Cloud: AWS, GCP, Azure • Big Data: Spark, Hive, Hadoop, Dask • Data: Pandas, NumPy, SQL databases, vector databases (Pinecone, ChromaDB) 🏆 𝐏𝐑𝐎𝐕𝐄𝐍 𝐑𝐄𝐒𝐔𝐋𝐓𝐒 ✅ 𝐔𝐧𝐢𝐭𝐞𝐝𝐇𝐞𝐚𝐥𝐭𝐡 𝐆𝐫𝐨𝐮𝐩 ➤ Leading ML system development that automates claim review processes, reducing manual workload ➤ Built foundation model for medical claims embeddings using Transformer architecture and multi-instance learning ➤ Developed RAG-based chatbot using GPT-3.5 with call center transcripts as knowledge base ➤ Created attention-based deep learning model for personalized patient care-path prediction (patent filed) ➤ Shipped CatBoost model for automated claim adjudication ✅ 𝐓𝐚𝐫𝐠𝐞𝐭 ➤ Implemented item2vec neural embeddings powering personalization for all Target guests ➤ Developed hierarchical item2vec algorithm incorporating product taxonomy in production ➤ Built recommendation diversification algorithms improving customer engagement ✅ 𝐆𝐞𝐧𝐞𝐫𝐚𝐥 𝐌𝐢𝐥𝐥𝐬 ➤ Deployed ARIMA and regression forecasting models on GCP for all North American products ➤ Created commodity price forecasting system scaled to 20+ commodities ➤ Built search algorithm for historical crop year similarity analysis in production ✅ 𝐌𝐞𝐝𝐭𝐫𝐨𝐧𝐢𝐜 & 𝐒𝐭𝐚𝐫𝐤𝐞𝐲 ➤ Developed ML algorithms for FDA-cleared implantable medical devices ➤ Built seizure detection system using spectral features from neural signals ➤ Created fall detection and respiratory monitoring algorithms using sensor fusion ➤ 6 patents granted/pending for neural signal processing innovations 🎓 𝐂𝐑𝐄𝐃𝐄𝐍𝐓𝐈𝐀𝐋𝐒 • Ph.D. Biomedical Engineering (Neural Engineering) — University of Minnesota • M.S. Computer Science (Data Science) — University of Illinois Urbana-Champaign, 4.0 GPA • B.S. Bioengineering — UC Berkeley • 6 Patents in AI/ML and medical device algorithms • 15+ Publications in peer-reviewed journals and conferences • Certifications: Pretraining LLMs, Generative AI with LLMs, Deep Learning for Healthcare, plus 30+ specialized courses 🌍 𝐈𝐃𝐄𝐀𝐋 𝐏𝐑𝐎𝐉𝐄𝐂𝐓𝐒 ✔ LLM/RAG application development (chatbots, Q&A systems, document processing) ✔ Healthcare AI and clinical data science ✔ Custom ML model development and deployment on AWS/GCP ✔ NLP pipelines and text analytics systems ✔ Recommender systems and personalization engines ✔ Time-series forecasting and predictive modeling ✔ ML architecture consulting and technical advisory I've led teams of data scientists and engineers, mentored junior practitioners, and collaborated with business stakeholders at every level. I understand that great technical work means nothing if it doesn't solve the actual business problem. Ready to discuss your project?

🏆 Top Rated Plus 🌟 100% Job Success 🤝 Satisfied Clients ⏱ Quick Turnaround 📞 Clear Communication Why work with me? Proven Experience: 💎 Backed by 15+ years of delivering results through scalable, cost-efficient data solutions. Technical Expertise: 💎 AI-Data Architecture: I deliver real-world-ready data through automated, reliable pipelines. The new AI era requires a new data platform. 💎 Conversational Analytics & AI Agents: Enable users to chat with their data through AI-driven interfaces. Google Conversational Analytics API and Gemini Enterprise 💎 Data Visualization: Skilled in Looker, Looker Studio, Power BI, Tableau, Superset, and others. 💎 Data Web Portals: Skilled in developing custom embeddable solutions and full web platforms under your own brand and domain. 💎 Database Management: Expertise in SQL (BigQuery, SQL Server, Oracle, MySQL, PostgreSQL, Snowflake) and NoSQL systems. 💎 ETL: Experience with both streaming and batch pipelines using Airflow, Apache Beam, Kafka, Debezium, Pub/Sub, and others. 💎 Data Modeling: Proficient with dbt, Dataform, and PySpark. 💎 Version Control: Comfortable with Git-based tools (GitHub, Bitbucket, GitLab, Azure DevOps). 💎 Cloud Platforms: Certified and experienced in GCP, AWS, and Azure. 💎 Unstructured Data: JSON, XML, Excel, Google Sheets. 💎 GA4 Data: Google Analytics 4 for advanced analysis. Soft Skills & Work Ethic: 💎 Versatile & Adaptive: Quick to learn new tools, roles, and business domains. 💎 Value-Driven: Focused on delivering high-impact outcomes with cost-efficiency. 💎 Detail-Oriented: Committed to precision and quality in every task. 💎 Reliable & Time-Conscious: Consistent delivery of high-quality work on time. 💎 Leadership: Capable of guiding teams and leading initiatives when needed. 💎 Analytical: Skilled at breaking down complex problems and finding effective solutions. 💎 Collaborative: Strong team player, effective in multidisciplinary environments. Scalable Technical Capacity: I’m supported by a network of 15+ specialists, including Solution and Data Architects, Developers, Designers, Process Specialists, DevOps Engineers, Machine Learning Engineers, Data Scientists, Data Analysts, and more. We work collaboratively to ensure your project receives the strongest possible technical support, from strategy to execution. How I approach projects: - Kick-off meeting to review requirements and deliverables - Action plan development using a project management tool - Weekly demo meetings to showcase progress - Detailed time and task tracking - Continuous feedback loop to ensure alignment and improvement - Complete documentation of the solution