👋 Hi, I’m Affaan: a Top Rated Plus Data Engineer & AI Solution Architect I specialize in building scalable data pipelines, optimizing cloud data architecture, and delivering powerful dashboards with Tableau/Power BI including translating AI capabilities, limitations, and business value into actionable insights to ensure alignment with project objectives. My Core Skills: 🔹 Generative AI & LLM Solutions Designing and implementing LLM-powered applications (e.g., chatbots, document processing, knowledge assistants) using modern frameworks. Working with prompt engineering, retrieval-augmented generation (RAG), vector databases, and AI orchestration tools to build production-ready intelligent systems. 🔹 Data Engineering: • ETL/ELT workflows using Python, dbt, Fivetran, AWS Glue, Azure Data Factory, Databricks • Data pipeline orchestration, cleansing, transformation, and automation • Cloud platforms: AWS, GCP (BigQuery), Azure 🔹 Data Visualization & BI: • Interactive dashboards in Power BI and Tableau • Metrics design, KPI tracking, and executive reporting • Business storytelling with clean visual narratives 🔹 Data Architecture & Management: • SQL & NoSQL design, performance optimization • Real-time streaming (Kafka, Spark Streaming) • Scalable data lakes, warehouse modeling 📈 Why Choose Me: ✅ Top Rated Plus on Upwork in under 1 year. ✅ Strong communicator who adapts to business context. ✅ Delivered for real estate, telecom, manufacturing, and healthcare clients. ✅ Focused on clean, tested, and production-grade solutions. Ready to Solve Your Data Challenges? Whether you need: • dbt models built on BigQuery • Tableau dashboards for your exec team • End-to-end pipeline from Fivetran to warehouse to dashboard I’m here to help. 📅 Let’s talk — I respond fast and deliver faster.

I build the clean, reliable data layer your team — and your AI tools — actually trust. From marketing, finance & CRM warehouses in BigQuery to real-time pipelines running at 200k+ events/sec, I've spent 15 years making data fast, accurate, and cost-effective. Most "data problems" aren't really about tools — they're about numbers finance can't trace, dashboards that silently break, and cloud bills that climb faster than the data does. I fix the layer underneath so the whole thing just runs — and often cut the bill while doing it. ⎯⎯⎯ What I do for you ⎯⎯⎯ ◆ Modern Warehouses in BigQuery (dbt + Medallion) — Unified, documented, AI-ready data from ad platforms (Meta, Google, TikTok), CRMs, and ERPs. For enhanza I consolidated financial data from 1,000+ organizations into one BigQuery platform with self-serve dashboards. ◆ AI-Ready & LLM Pipelines — Data modeled so your AI tools consume it directly: LLM enrichment/categorization, clean context windows, no manual prep. Shipped code-first with Claude Code + gcloud — no hand-written SQL in the console. ◆ Cut Your Cloud Bill (FinOps) — Runaway AWS costs are usually egress fees and over-priced managed services, not the data itself. I migrated a client's Dagster pipelines from AWS to Civo Kubernetes + Cloudflare R2 — eliminating S3 egress fees and slashing managed-cluster costs, with no orchestration rewrite. If your bill is climbing, I'll audit it and re-architect the expensive parts. ◆ Real-Time & High-Scale (when you need it) — Streaming in Flink/Kafka and sub-second OLAP in ClickHouse/StarRocks. I've run 200k+ ingest events/sec in an air-gapped cluster — so a standard pipeline is routine for me. ◆ Reliability & Observability — Monitoring, lineage, and schema-drift alerts so dashboards stop breaking. On one platform this cut data downtime by ~90%. ⎯⎯⎯ How I work ⎯⎯⎯ ▹ Root-cause, not patches. I fix the layer underneath so the same dashboard doesn't break again next month. Quick patches are how data platforms rot. ▹ Built to run without me. No "works once on my laptop" scripts — proper deployment, secrets, logging, alerts, and infrastructure as code (Terraform). Reproducible, and yours to keep. ▹ Straight about what I know. If something's outside my wheelhouse, I say so up front and give you the honest trade-off. I won't learn on your budget and call it experience. ▹ I own the outcome. Give me the goal and I'll work through the ambiguity and keep you posted — no micromanagement needed. ▹ A full team behind me. I run with a ~20-person team across data engineering, BI, DevOps, and AI/ML — so you're never betting on one person's calendar or blind spots. You work with me directly, and I pull in the right specialist when the scope calls for it. Senior ownership, agency depth. ⎯⎯⎯ Tech I work in daily ⎯⎯⎯ ▹ Warehouse & Analytics: BigQuery, dbt, dlt, Meltano, Medallion Architecture, Power BI, Looker Studio, Metabase ▹ Cloud & Orchestration: GCP, AWS, Azure, Civo, Airflow, Prefect, Dagster, Kubernetes, Terraform ▹ Streaming & Performance: Kafka, Flink, Spark/PySpark, ClickHouse, StarRocks, Iceberg, Delta, Polars, Cloudflare R2 ▹ AI-first delivery: Claude Code + gcloud/CLI, LLM enrichment pipelines ⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯ I don't just "install tools" — I design for compute cost (FinOps) and data reliability. If your cloud bill is climbing or your reporting can't be trusted, I'll audit the stack and tell you exactly what to fix. Want a quick, no-pressure look at your setup? Send me a message and I'll share where I'd start.

I’m passionate about combining Data Engineering, AI & Dashboards Design Science to help people make great decisions. Through thoughtful design, including UI & UX, and precise data analysis, I connect how data looks with how it works. With over six years of experience in behavioral data analysis and storytelling, I’ve consistently delivered impactful solutions. Recently, I’ve received over 50 ⭐️⭐️⭐️⭐️⭐️ ratings for my work in data visualization. My expertise is in Data Engineering, Analysis, Visualization, Storytelling, and Infographics. I focus on promoting a data-driven culture in companies around the world by upholding the principles of Graphical Excellence, as championed by Tufte. My motto is - data never lies. 🤘 SORRY FOR THE LONG TEXT BELOW, BUT I NEED THIS SECTION OF MY PROFILE TO HELP ME STAND OUT ON UPWORK. ✌️😃🤷‍♂️ Here's a list of my preferred tools, categorized by their respective functions: Dashboarding: Power BI ( including pbiviz), powerbi Looker, Looker BI, Looker Enterprise, Looker Pro, Google Data Studio, Looker Data Studio, Tableau, ThoughtSpot (Thought Spot), Metabase, Domo Dashboards (domo com), Superset Apache, Plotly, Plotly Dash, Plotly Dash Enterprise, Dash Enterprise, D3.js, Aesthetic dashboards TOP Niche Expertise: Smartsheet .com Ecommerce: shopify, bigcommerce Construction (buildertrend, builder trend) Hyros, triple whale Stripe, Rebilly, Chargebee GA4 (Google Analytics 4), Bullhorn, Sage, Microsoft Dynamics CRM (BI graphs), Exact com/ Exact ERP, Multi-Tenant BI Solution / Multi-Tenant Dashboards, AI ( Artificial Intelligence, A.I.). Data Warehousing: Google BigQuery, Amazon Redshift, Redshift Snowflake, Microsoft Azure Synapse Analytics, Data Modeling: dbt (Data Build Tool), SQL Server Data Tools (SSDT), Python. Additional tags: SSRS report, Data Analysis Expressions (DAX), Revenue Operations, Microsoft Azure SQL Server, web3, business intelligence, Software as a service (SaaS), Microsoft Graph API, coaching, data science, Microsoft Power BI, Looker Studio, Excel, Tableau Alteryx, Inc.Database, Data Analysis, Google Analytics, Dashboard, Data Analysis, A/B Testing, Data Visualization, Google Analytics, Marketing Analytics, Analytics, API Integration, JavaScript, Tableau, Microsoft Excel, Python, Data Analysis, Data Science, Statistics, Business Intelligence, PowerBI, Training & Development, API integration, Customer Relationship Management (CRm), CRM, Zoho CRM, API Integration Digital Mapping, AnyLogic, Looker Studio, Data Visualization, App Store, BigQuery, Marketing Analytics, Ad analytics, CRM, prometheus io, Microsoft Graph API, SAP, SAP Analytics, sap analytics cloud, Oracle BI, multi-tenant, multi-tenant Dashboards, multi-tenancy, Microsoft Power Apps, Power Query, LookML, IBM Cognos Analytics, SaaS, SEMrush, Python, Supermetrics, NetSuite, Oracle NetSuite, Qlik Sense, QlikView, Gaming, Behavioral analytics, events analytics, ETL Pipeline, quantitative analyst, quantitative analytics, Bullhorn, pbiviz, LMS, MicroStrategy, Micro Strategy, construction, eNPS, NPS, green energy, Excel, Hadoop, Thoughtspot, AI, artificial intelligence, KPIs, data science, behavior, Spark, Hadoop, Python, Zoho, Problem-Solving Abilities, Strong analytical skills, NetSuite, NS, Sisense, Cognos, Power apps, Powerapps, Amazon Quicksight, QuickSight, IBM Z platform, Cognos, DB2, Luzmo, CRMA, CRMA Analytics Salesforce, Holistics io, Holistic io, Loki, Prometheus, BI meta-data management, Microsoft Power BI Data Visualization, Oracle, Sigma, Sigma Computing, US, USA, PL/SQL, Oracle PL/SQL, dbt, looker ML, construction, Archdesk, Archdesk ERP, Apache Airflow, Flask, Django, Docker, Apache Spark, SAP Crystal Reports, Open AI, ChatGPT, Chat GPT, AWS, Claude, Bedrock, Paycor, BambooHR, Workday, Zenefits, ClickUp, AI, Artificial intelligence, ClickHouse, Click House, ROAS, ROMI, Domo, Gooddata, Good Data, Omni, Omni Analytics, Oracle Hyperion, power bi embedded, embedded analytics, databox, Row Zero, local LLM deployment, LLM (large language model), filevine, data lake, data warehouse, hubspot, Knowi, Fivetran, Airbyte, CDP, Bayesian Analysis, Predictive Analytics, Dremio, Apache Ozone, Looker Core, Copilot, Tibco Spotfire, React, AI/LLM, charts io, PostgreSQL, React.js, AI-driven, Python, healthcare, gooddata, good data, NetSuite Commerce, NetSuite, Domo, OpenAI, power apps, Interactive Data Visualization, Data Visualization Framework, looker ml, observable, UX/UI design, Xero, QuickBooks, Intuit, Sage, RevOps, revenue operations, Power BI, Microsoft Power BI, Tableau, google analytics, GA4, looker studio, shopify, triple whale, Buildertrend, Go High Level, GoHighLevel, ThoughtSpot, Spotfire, Power BI Report Server, flourish, copiliot studio, Palantir Foundry, Palantir Gotham, Palantir Apollo, , Snowflake Native App, revops, australia, ), AI automation Construction, contractors, Construction Technology: Primavera P6, Procore, Autodesk, Service Titan, Buildertrend, Netsuite

Hi, I'm Owais. I've spent 7+ years building data systems across enterprise and startup environments. I've set up entire data platforms from end-to-end on AWS, Azure, and GCP, including in SOC 2 and HIPAA environments. I've built ETL pipelines that don't break at 3 AM, modeled warehouses that survive contact with real business logic, and shipped dashboards people actually open. These days I help growth-stage startups build analytics platforms around AI without bleeding money on it. Natural language to SQL, agents that surface insights instead of waiting to be asked, automated anomaly detection, the kind of features your customers are starting to expect. Most AI-in-analytics projects don't fail because the model isn't good enough. They fail because the foundation underneath it is a mess. A well-documented dbt project does more for AI accuracy than a bigger LLM, and if your dashboards aren't getting opened, adding AI on top doesn't change anything. If you're trying to build AI-powered analytics and want someone who's done the unglamorous work that makes it actually useful, let's talk.

𝗔𝘇𝘂𝗿𝗲,𝗙𝗮𝗯𝗿𝗶𝗰,𝗕𝗶𝗴𝗤𝘂𝗲𝗿𝘆 𝗮𝗻𝗱 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀 𝗖𝗲𝗿𝘁𝗶𝗳𝗶𝗲𝗱 Data Engineer & Data Architect with 𝟭𝟬+ 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 in 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴, 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴, 𝗗𝗮𝘁𝗮 𝗟𝗮𝗸𝗲𝗵𝗼𝘂𝘀𝗲, 𝗘𝗧𝗟/𝗘𝗟𝗧, 𝗗𝗮𝘁𝗮 𝗠𝗼𝗱𝗲𝗹𝗶𝗻𝗴, 𝗗𝗮𝘁𝗮𝗯𝗿𝗶𝗰𝗸𝘀, 𝗦𝗻𝗼𝘄𝗳𝗹𝗮𝗸𝗲, 𝗔𝗪𝗦, 𝗔𝘇𝘂𝗿𝗲 & 𝗚𝗖𝗣. I build scalable Data Pipelines, Cloud Data Warehouses, Lakehouses and BI solutions using 𝗣𝘆𝗦𝗽𝗮𝗿𝗸, 𝗦𝗤𝗟, 𝗱𝗯𝘁, 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜, 𝗧𝗮𝗯𝗹𝗲𝗮𝘂 & 𝗟𝗼𝗼𝗸𝗲𝗿 𝗦𝘁𝘂𝗱𝗶𝗼. Why Work with Me? 🏆 𝗧𝗼𝗽 𝗥𝗮𝘁𝗲𝗱 𝗣𝗹𝘂𝘀 𝗙𝗿𝗲𝗲𝗹𝗮𝗻𝗰𝗲𝗿 𝘄𝗶𝘁𝗵 𝟭𝟬+ 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝗶𝗻 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗮𝗻𝗱 𝗔𝗜 ⭐ 𝗢𝘃𝗲𝗿 𝟱𝟬 𝗰𝗹𝗶𝗲𝗻𝘁𝘀 𝘄𝗶𝘁𝗵 𝟱 𝘀𝘁𝗮𝗿 𝗿𝗮𝘁𝗶𝗻𝗴𝘀 ⏱ 𝟯𝟭𝟬𝟬+ 𝗵𝗼𝘂𝗿𝘀 𝗹𝗼𝗴𝗴𝗲𝗱 𝗼𝗻 𝗨𝗽𝘄𝗼𝗿𝗸 ✔ 𝗛𝗮𝗻𝗱𝘀 𝗼𝗻 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝗦𝘁𝗮𝗿𝘁𝘂𝗽𝘀 𝘁𝗼 𝗟𝗮𝗿𝗴𝗲 𝗦𝗰𝗮𝗹𝗲 𝗘𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗗𝗮𝘁𝗮 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀 My Expertise Includes: ✔ Google Cloud: Google Sheets, Analytics, Tag Manager, BigQuery, Cloud Function, Dataflow, Pub/Sub, Storage Bucket, Looker ✔ Microsoft Azure: Datalake Gen2, Blob Storage, Data Factory, Synapse, Analysis Services, SQL Data Warehouse, Event Hub, Databricks ✔ Microsoft: T-SQL, SSIS, SSAS, Power BI ✔ Amazon Web Services (AWS): S3, DynamoDB, Kinesis, RDS, Redshift, Glue, Lambda ✔ Other Tools: Databricks, Snowflake for Delta Lakehouse, DBT, SQL, Python I’ve designed and implemented data architecture for Fortune 50 to 500 companies, providing customized solutions that meet complex data challenges. If you're looking for a data expert to help transform your data into actionable insights, let’s connect! I'm just one message away and excited to work with you.

💪 𝗦𝗲𝗻𝗶𝗼𝗿 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 | 𝗔𝗜 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 | 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝘁𝗶𝘀𝘁 | 𝗤𝘂𝗮𝗻𝘁 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 𝗙𝗶𝗻𝗮𝗻𝗰𝗲, 𝗘𝗰𝗼𝗻𝗼𝗺𝗶𝗰𝘀 𝗣𝗵𝗗 I design and build data infrastructure, AI-powered systems, and quantitative models that turn complex data into measurable business and financial outcomes. 𝙈𝒚 𝒘𝙤𝒓𝙠 𝙨𝒊𝙩𝒔 𝒂𝙩 𝙩𝒉𝙚 𝙞𝒏𝙩𝒆𝙧𝒔𝙚𝒄𝙩𝒊𝙤𝒏 𝒐𝙛: Quantitative Analysis & Energy Markets — 15+ years of advanced modeling, forecasting, and risk management Machine Learning & AI Systems — End-to-end ML pipelines, LLM integration, and AI agent development Data Engineering & Analytics Infrastructure — Scalable pipelines from ingestion to decision layer Automation & Intelligent Workflows — Process automation that eliminates manual bottlenecks 𝑹𝙚𝒄𝙚𝒏𝙩 𝙛𝒐𝙘𝒖𝙨 𝙖𝒓𝙚𝒂𝙨 𝙞𝒏𝙘𝒍𝙪𝒅𝙚: - Building and deploying AI agents and LLM-powered document processing systems (Vertex AI, Gemini, LangChain, CrewAI) - Designing end-to-end data platforms on Snowflake, Databricks, BigQuery, and Redshift - Developing automated trading strategies and quantitative execution systems - Creating real-time dashboards and reporting with Power BI, Tableau, and Streamlit - Implementing workflow automation using Power Automate, Airflow, and custom API integrations - Integrating ML models into production — from feature engineering to serving and monitoring 𝑪𝙤𝒓𝙚 𝙩𝒆𝙘𝒉𝙣𝒊𝙘𝒂𝙡 𝙨𝒕𝙖𝒄𝙠: - Cloud & Infrastructure: GCP (Vertex AI, BigQuery, Cloud Functions), AWS (S3, Lambda, Redshift), Azure - Data Engineering: Snowflake, Databricks, Apache Spark, dbt, Airflow, Kafka - ML / AI: Python, TensorFlow, PyTorch, scikit-learn, LangChain, Hugging Face, OpenAI/Gemini APIs - Automation: Power Automate, Zapier, n8n, custom REST/GraphQL integrations - Visualization: Power BI, Tableau, Streamlit, Plotly - Languages: Python, SQL, R, JavaScript Published researcher with multiple peer-reviewed articles in energy economics and risk modeling. Leadership experience spanning industry and academia, including curriculum development and team management. I work best with founders, operators, and technical teams who need systems built — not decks delivered.

I am Data & AI Architect with 12+ years of experience across multiple sectors, currently focusing on modern data stacks and building efficient data layers for AI use cases My experience related to enterprise level and high profile projects in the past, but now I'm helping startups and small-mid sized companies to achieve their goals! My core competences are: Data Modeling, Data Architecture on Cloud platforms, Data Integration and AI Data layers, ETL and Business Intelligence, Database Administration Solution Architecture : Design of solution architectures for a data processing systems of various scale and purpose. Definition of modern stack technical solutions including data storage, network, data processing (ELT/ETL), BI and AI/ML components. Process and methods definitions and optimizations AI/ML : Amazon Quicksuite, LLM API Integration (OpenAI, Gemini, Antropic), AWS Sagemaker, pgvector, Databricks Mozaic AI, Snowflake Cortex/Agents Data Modelling : Modelling of OLTP and Datawarehouse systems. It could be design of new schema, normalization/denormalization of existing model, Enterprise datawarehouse design based on Kimball/Inmon, Data Lake and Data Vault architectures, Modernization of existing data landscape Data Lakes : Modern datalakes built on cloud storages as GCS/S3/Azure Datalake Gen2 with Databricks, AWS Glue, Trino, Apache Iceberg DBA Activities : DB migrations, Backup & Recovery, Upgrades, Instance configurations, DB Monitoring, Horizontal scaling, Streaming/BDR replications. Sharding with postgreSQL extensions Data Integration and ETL : Traditional batch ETL - Informatica, Talend, AWS Datapipeline, Matillion ETL Serverless ETL - AWS Lambda, AWS Glue, Batch, AWS DMS, Google Cloud Functions, Databricks Streaming ETL - Apache NiFi, Kafka, Kinesis streams SaaS ETL - Stitch, Alooma, Fivetran, Airbyte BI/data miodeling layers - dbt/Dataform/Prefect Direct loading with DBMS tools & scripting Data Governance and MDM: Design and implementation of solutions based on Informatica DG/MDM, Alation, Atlan, Azure Purview and custom dataquality solutions BI Systems : Design of BI systems and implementation. I had experience with major industry leading tools as Tableau, PBI, Looker and cloud alternatives. Additionally i had experience with old-style reporting solutions from SAP, Qlick, Jasper Cloud containerization and deployment : Docker, Mesos/Kubernetes Java development : EE/SE , Spring, Hibernate, RESTful APIs, Maven Clouds : - Cloud migrations (AWS, Azure, GCP) - Cloud infrastructures (VPCs, EC2, Loadbalancing, Autoscaling, Security in AWS/GCP) Please note that minimum engagement is part-time (20 hrs/week), this will ensure the quality of delivered solution and mutual benefit. Thank you for getting to the end of this extensive details and looking forward working on a project together :) Best Regards, Yegor.

I am a dedicated Data Engineer with a strong foundation in data analytics, specializing in building production-grade data infrastructure, distributed database systems, scalable ETL pipelines, and AI-powered data applications. With 7 years of experience, I help companies: • Transform messy data into automated, reliable, and scalable ETL pipelines for complex financial data that save 100+ hours monthly • Architect distributed database systems: Design multi-tier data architectures for massive-scale record management • Build advanced ETL pipelines with intelligent change detection to process only what's changed, reducing unnecessary processing • Architect cloud-native data solutions and scale data infrastructure across multiple clouds • Automate data workflows to eliminate manual processing and escape Excel Hell • Build Information Retrieval (IR), semantic search, OpenSearch, and Retrieval-Augmented Generation (RAG) systems that make massive datasets, documents, and knowledge bases searchable and actionable • Develop AI-powered data applications, including document intelligence, chatbot, and agent-based solutions integrated with existing business workflows • Modernize legacy data systems with cloud & AI solutions • Optimize data infrastructure to reduce costs and improve performance • Design parallel execution frameworks: Implement isolation patterns enabling concurrent pipeline runs without conflicts • Build data foundations for AI initiatives, including vector search, knowledge retrieval, document processing, and AI automation workflows I have been providing a wide range of services in the realm of data analytics and data engineering such as: • ETL/ELT pipeline orchestration: Prefect, Databricks Workflows & Asset Bundles • Lakehouse & distributed database architecture: Databricks/Delta, YugabyteDB (distributed PostgreSQL), Neo4j, OpenSearch • Custom dbt materializations and incremental models: SCD-2, temporal tables • Database optimization and storage compression • Data validation, quality quarantine & reconciliation frameworks • Per-run schema isolation and parallel pipeline execution • Google Sheets automation and dashboard generation • Excel-to-database migration and formula translation • Multi-source data integration: CSV, Parquet, S3, APIs, databases • Data Cleaning & Transformation at scale • Operational Efficiency Analysis • Financial metrics calculation systems • Multi-cloud architecture design • Infrastructure as Code • Cloud services integration: AWS, GCP, Azure • RAG & LLM data applications: grounded citations, document extraction, NL-to-SQL semantic layers • Automated reporting solutions (Python-Excel integration) • Data Visualization & Dashboarding While the above services encapsulate my core offerings, I am inherently adaptable and thrive on diving into new challenges and expanding my skill set. Seeking great, enthusiastic projects that will provide me with challenging, interesting work that I can learn from and contribute to. My stack: Data Engineering: ✅ Python ✅ SQL (PostgreSQL, MySQL, SQL Server, YugabyteDB, DuckDB) ✅ Prefect ✅ dbt ✅ PySpark ✅ Delta Lake ✅ Databricks Cloud & Infrastructure: ✅ AWS (EC2, S3, Glue, RDS, Lambda, EKS, DynamoDB, ECR, Bedrock) ✅ Google Cloud Platform (BigQuery, GKE, Bigtable, Cloud Functions) ✅ Azure (ADF, Synapse, AKS, Cosmos DB, Azure Functions, ACR, Text Analytics) ✅ Terraform ✅ Docker ✅ Kubernetes ✅ Prometheus Data Storages: ✅ RDBMS (PostgreSQL, MySQL, SQL Server, DuckDB) ✅ Object Storage (S3, Wasabi) ✅ Graph Database (Neo4j) ✅ Key-Value Database (Redis, DynamoDB) ✅ Document Database + Search Engine (OpenSearch) ETL & Data Processing: ✅ Pandas ✅ NumPy ✅ Selenium ✅ BeautifulSoup Spreadsheet Automation: ✅ Google Sheets API (gspread) ✅ Excel automation (openpyxl, xlwings) ✅ Automated dashboard generation Data Visualization: ✅ Matplotlib ✅ Seaborn ✅ Plotly ✅ Power BI ✅ Grafana Backend Development: ✅ FastAPI ✅ Flask ✅ RESTful APIs ✅ GraphQL ✅ Redis ✅ Nginx ✅ Gunicorn ✅ WebSocket AI/LLM & Agent Systems: ✅ OpenAI API ✅ Anthropic API ✅ Gemini API ✅ AWS Bedrock ✅ Agent Development ✅ AI Chatbots ✅ RAG ✅ NL-to-SQL semantic layers ✅ Semantic search

I help businesses 𝐭𝐮𝐫𝐧 𝐜𝐨𝐦𝐩𝐥𝐞𝐱, 𝐬𝐜𝐚𝐭𝐭𝐞𝐫𝐞𝐝 𝐝𝐚𝐭𝐚 𝐢𝐧𝐭𝐨 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞𝐝 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬, 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐄𝐓𝐋 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, and real-time analytics systems that eliminate manual reporting and enable faster, smarter decision-making. I specialize in building 𝐞𝐧𝐝-𝐭𝐨-𝐞𝐧𝐝 𝐝𝐚𝐭𝐚 𝐞𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐚𝐧𝐝 𝐀𝐈-𝐩𝐨𝐰𝐞𝐫𝐞𝐝 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬 𝐮𝐬𝐢𝐧𝐠 𝐀𝐖𝐒, 𝐁𝐢𝐠𝐐𝐮𝐞𝐫𝐲, 𝐒𝐐𝐋, 𝐏𝐲𝐭𝐡𝐨𝐧, 𝐚𝐧𝐝 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈, helping companies move from fragmented data systems to fully automated data ecosystems. With 7+ years of experience in 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 𝐚𝐧𝐝 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞, I design and implement scalable, cloud-based data solutions including data pipelines, data warehouses, reporting systems, and workflow automation architectures. I have successfully delivered 250+ projects for startups, SMEs, and enterprise clients across industries such as finance, SaaS, e-commerce, healthcare, logistics, and operations, consistently improving reporting speed, data accuracy, and business visibility. Whether you need automated dashboards, cloud data pipelines, data warehouse solutions, or reporting systems, I can help you build a reliable and scalable data infrastructure that supports better decision-making. 📌𝐒𝐄𝐑𝐕𝐈𝐂𝐄𝐒 𝐈 𝐎𝐅𝐅𝐄𝐑 📊 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 & 𝐁𝐈 𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬 ◼Executive & KPI dashboards (Finance, Sales, Operations) ◼Advanced DAX calculations & Power Query (M) ◼Row-Level Security (RLS) ◼Data modeling (Star & Snowflake schema) ◼Automated reporting systems ⚙️ 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 & 𝐄𝐓𝐋 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬 ◼ETL/ELT pipelines using Python, SQL, PySpark ◼API & multi-source data integration ◼Data transformation workflows (dbt) ◼Data validation & quality frameworks ◼Performance optimization ☁️ 𝐂𝐥𝐨𝐮𝐝 𝐃𝐚𝐭𝐚 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 ◼AWS (S3, Glue, Redshift, Lambda) ◼Google BigQuery ◼Snowflake & Databricks ◼Azure Data Factory ◼Data warehouse design & migration 📈 𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐈𝐦𝐩𝐚𝐜𝐭 ◼50–70% reduction in manual reporting effort ◼Real-time dashboards for leadership decisions ◼Scalable and secure data architecture ◼Single source of truth across all systems ◼Faster, data-driven decision making 🛠 𝐓𝐄𝐂𝐇 𝐒𝐓𝐀𝐂𝐊 Power BI | SQL | Python | PySpark | AWS | BigQuery | Snowflake | Azure Data Factory | Databricks | dbt | ETL Pipelines | Data Warehousing | API Integration | Data Modeling | DAX | Power Query 🤝 𝐖𝐡𝐨 𝐈 𝐖𝐨𝐫𝐤 𝐖𝐢𝐭𝐡 𝐈 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡: ✔Startups scaling their data systems ✔SMEs needing automated reporting ✔Enterprises modernizing legacy data pipelines ✔Teams struggling with messy spreadsheets or disconnected data 💡 𝐖𝐡𝐲 𝐂𝐥𝐢𝐞𝐧𝐭𝐬 𝐇𝐢𝐫𝐞 𝐌𝐞 I focus on building production-grade data systems that are scalable, automated, secure, and easy to maintain. My goal is not just to create dashboards, but to help businesses make faster, smarter, and data-driven decisions with confidence. 𝐈𝐟 𝐲𝐨𝐮 𝐧𝐞𝐞𝐝 𝐚 𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫 𝐨𝐫 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 𝐰𝐡𝐨 𝐜𝐚𝐧 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐞 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬, 𝐨𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐫𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐛𝐮𝐢𝐥𝐝 𝐬𝐜𝐚𝐥𝐚𝐛𝐥𝐞 𝐝𝐚𝐭𝐚 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬, 𝐬𝐞𝐧𝐝 𝐦𝐞 𝐚 𝐦𝐞𝐬𝐬𝐚𝐠𝐞 𝐰𝐢𝐭𝐡 𝐲𝐨𝐮𝐫 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐝𝐞𝐭𝐚𝐢𝐥𝐬.

I’m an ex-Shopify data scientist and analytics engineer with 6+ years of experience, currently working at CoinBase. At Shopify I worked on production-scale analytics systems across the data warehouse ecosystem; ingestion, storage, data modelling, and analytics. I now help businesses design and build data warehouses. I fix storage and ingestion issues, implement data governance, design and orchestrate data modeling, and build analytics workloads for your team. I mostly work in the Google ecosystem (GCS, BigQuery, Looker), but can use whatever platform your business needs (e.g., Databricks, Snowflake, Microsoft Azure, etc.) I have a Databricks certification, as well as have developed hundreds of dashboards across all the different platforms. Why clients hire me: ✅ Deep data platform knowledge (3 years at Shopify) ✅ Clear communication + Loom walkthroughs ✅ Fast turnaround with clean, documented work ✅ End-to-end expertise: tracking, data pipelines, and dashboards If you have a broken pipeline, or need one to be built, please reach out, I'd love to help.