Power BI developer + Data Engineering — I build the automated pipelines (Databricks, ADF, SQL, Fivetran) and the dashboards leadership trusts, end to end. If your team is still pulling numbers by hand, stitching exports together, and quietly not trusting what's in the report — your data isn't slow, it's unbuilt. And every decision made on top of it is shakier than it should be. I'm a data engineer and BI specialist with 13+ years building the full path from raw, messy source data to the dashboards leadership actually trusts. Co-founder of GrowthBI, an analytics consultancy serving scaling companies across Australia, Europe, and the US. Here's what makes me different: most freelancers do one half. Pure data engineers hand you clean tables and no story. Pure dashboard builders make polished reports on top of data that breaks every week. I build both halves — the pipeline and the reporting — so you hire one person instead of managing two. 80%+ of my clients come back for follow-on work. Where I deliver the most impact: → Data pipelines & automation — Fivetran, DBT, SQL pipelines that ingest from SAP, CRMs, ad platforms, and spreadsheets, model the data in Databricks/BigQuery, and refresh on a schedule so reports build themselves → Data modelling & warehousing — clean, documented, single-source-of-truth tables your whole team can rely on → Power BI & Looker Studio dashboards for marketing, product, sales, and finance leadership → Executive reporting — YTD, MTD, YOY, and scenario comparisons leadership can act on → Customer & growth analytics — RFM modelling, cohort analysis, churn prediction, CAC vs. LTV, channel attribution → Row-level security (RLS) & governance for multi-team and multi-entity reporting Results I've delivered: → Consolidated [X] disconnected sources into one automated pipeline — eliminated ~[X] hrs/week of manual reporting and gave leadership numbers they could finally trust → 10x growth in customer acquisition — surfaced channel-mix insights that reshaped how a leadership team allocated marketing spend → 10% churn reduction — identified the highest-risk customer cohort with RFM segmentation and built a live re-activation tracker for the sales team → Prevented significant revenue loss — caught a payment failure from a default product setting before it compounded, with a live monitoring dashboard run until the fix shipped My core stack: SQL · DBT · Fivetran · Databricks · BigQuery · Power BI · DAX · Power Query · Alteryx · SSIS · Excel Industries: E-commerce · SaaS · Real Estate · Financial Services · Insurance · Consumer Goods Clients I've worked with: Rate My Agent · Keep It Cleaner · Montgomery Homes · Peeplcoach · Paylater · Joolca I work directly with C-suite leaders, senior leadership teams, and cross-functional analysts. I understand what each team needs to answer — and I build the data layer and the dashboards that answer it, without a manual every time.

Are you looking to build high-performance data pipelines, automate workflows with AI, and track web analytics to maximize your ROI? You are in the right place. Hi, I am Faisal Ashraf, a certified Analytics & Data Engineer. I bridge the gap between raw data, cloud infrastructure, and business intelligence. Using the Modern Data Stack (Snowflake, dbt, Python, SQL, and Power BI), I build secure data pipelines, automate manual processes with AI, and deliver dashboards that drive revenue. Modern businesses cannot afford to rely on guesswork. Whether you need to clean messy data, migrate to Snowflake, build dbt models, or deeply analyze web traffic, I provide end-to-end data solutions that cut costs and save hours of manual work. --- 🛠️ Core Expertise & How I Can Help Your Business: 1. Cloud Data Engineering & Modeling (Snowflake & dbt) * Designing scalable, secure cloud data warehouses in Snowflake. * Building modular, tested, and documented data transformation pipelines using dbt (Data Build Tool). * Ingesting structured and semi-structured data (JSON, Parquet) with clean ETL/ELT processes. * Managing virtual warehouse compute resources to minimize Snowflake costs. 2. Data Automation & Analytics (Python, SQL & Power BI) * Writing advanced, optimized SQL queries for complex data extraction and analysis. * Developing Python scripts for data cleaning, API integrations, and workflow automation. * Creating interactive, automated Power BI dashboards with DAX to track business KPIs. 3. AI Workflow Integration (Google AI Certified) * Deploying Generative AI tools and custom prompt engineering to optimize operations. * Integrating smart AI models into existing business systems to eliminate bottlenecks. 4. Traffic & Web Analytics (Google Analytics Certified) * Setting up advanced Google Analytics (GA4) reporting and exploration dashboards. * Tracking user behavior, traffic acquisition channels, and conversion funnels. --- 🧰 Technical Toolkit: * Data Warehousing: Snowflake * Transformation & Orchestration: dbt (Data Build Tool) * Programming & Query Languages: Python, SQL * Business Intelligence: Power BI, Looker Studio * AI & Analytics: Google AI Tools, Google Analytics (GA4) --- 🎓 Verified Certifications: * Snowflake Data Engineering Professional Certificate * Google AI Professional Certificate * Google Analytics: Reports & Traffic Analysis (via Coursera) --- 🤝 Why Hire Me? * Industry-Vetted Standards: My skills are directly verified by Google and Snowflake, ensuring world-class best practices and data security. * Business-First Approach: I don’t just write queries; I focus on how my data models and dashboards will directly increase your business efficiency. * Clear Communication: I provide regular, jargon-free updates so you always know the exact progress of your project. --- 📈 My Working Process: 1. Discovery: A quick chat to understand your data architecture, business goals, and bottlenecks. 2. Strategy & Roadmap: Designing a tailored data/AI plan customized to your budget. 3. Execution & Testing: Writing clean code, building dbt models, and setting up error-free pipelines. 4. Handover: Providing complete documentation or video walkthroughs so your team can easily manage the system. Ready to unlock the true potential of your business data? Click the "Message" or "Invite to Job" button on the top right. Let’s schedule a quick 10-minute discovery call to discuss your project!

☑️ 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

I build marketing analytics platforms on BigQuery and dbt that turn fragmented ad, web, and ecommerce data into reliable reporting. I help marketing teams and agencies automate reporting, unify cross-channel data, improve attribution, and measure ROAS accurately. Core stack: BigQuery, dbt, GA4, Google Ads, Meta Ads, Shopify, Fivetran, Python, Power BI, and Looker Studio. SELECTED RESULTS ▪ Ecommerce brand: Replaced spreadsheet reporting with a BigQuery + dbt pipeline and Power BI dashboards. Reporting dropped from days to hours while the client scaled to $2M+/month in paid media with reliable ROAS tracking. ▪ US marketing agency: Consolidated 40+ ad accounts into one warehouse and implemented attribution models. Enabled weekly client reporting that reduced billing disputes and improved upsell conversations. ▪ Lead-gen company: Built a GA4 + server-side measurement pipeline and Looker Studio dashboards. Improved conversion tracking accuracy and identified duplicate conversions that were distorting campaign performance. WHAT I BUILD ▪ Analytics engineering: dbt models, testing, documentation, and reusable KPI definitions ▪ Data warehouses: BigQuery architecture, data modeling, partitioning, and cost optimization ▪ ELT pipelines: Fivetran, custom Python ingestion, APIs, Cloud Functions, and Cloud Run ▪ Marketing measurement: GA4, server-side events, attribution, ROAS, CAC, CPA, LTV, and conversion analysis ▪ Dashboards: Power BI and Looker Studio, designed for performance and decision-making ▪ Integrations: Google Ads, Meta Ads, Shopify, Amazon Ads/SP-API, HubSpot, Salesforce, Klaviyo, Stripe, TikTok Ads, LinkedIn Ads, Microsoft Ads, and more HOW I WORK I start with the business decisions your reporting needs to support, then trace each KPI back to its source. From there, I build and test the pipelines, define consistent business logic, and create the reporting layer. You get working deliverables throughout the project, plus documentation and a clean handover. I bring 10+ years of analytics experience and have built 100+ dashboards across marketing, ecommerce, operations, and executive reporting. LET'S TALK Tell me what you're trying to measure, where your data currently lives, and what you don't trust about your reporting. I'll help you identify where the measurement or data pipeline is breaking down and the most practical way to fix it.

Get reliable data pipelines, trusted dashboards, and a single source of truth your team can actually use. I’m a Senior Data Engineer and BI Consultant with 9+ years of experience designing, building, and maintaining modern data platforms across AWS, GCP, Microsoft Fabric, Power BI and Data Studio. I help businesses move from scattered files, broken pipelines, slow reports, and unreliable dashboards to clean, automated analytics systems that support faster and better decision-making. I specialize in cloud data engineering, data warehousing, lakehouse architecture, dbt transformations, and business intelligence solutions that are production-ready, scalable, and easy to maintain. 𝐇𝐞𝐫𝐞’𝐬 𝐖𝐡𝐚𝐭 𝐈 𝐂𝐚𝐧 𝐃𝐨 𝐅𝐨𝐫 𝐘𝐨𝐮: ✅ Design and build automated data pipelines across AWS, GCP, and Microsoft Fabric. ✅ Build modern data warehouses and lakehouses using Redshift, BigQuery, Databricks, Synapse, S3, and Apache Iceberg ✅ Develop clean transformation layers using dbt, SQL, PySpark, Python, and Power Query. ✅ Implement reliable data models using Kimball Multi-Dimensional Modeling, and Data Vault 2.0 ✅ Build streaming pipeline using Amazon MSK, and Kafka ✅ Build executive dashboards in Power BI, Looker Studio, Tableau, Excel, and Google Sheets. ✅ Improve slow reports, broken pipelines, poor data quality, and unreliable analytics workflows. ✅ Document systems clearly so your team can understand, maintain, and scale them. 𝐒𝐤𝐢𝐥𝐥𝐬 𝐓𝐡𝐚𝐭 𝐌𝐚𝐭𝐭𝐞𝐫: ➡️ Cloud Data Engineering: AWS, GCP, Microsoft Fabric, Azure ➡️ Data Warehousing: Redshift, BigQuery, Snowflake, Synapse Analytics ➡️ Data Lakes & Lakehouse: Amazon S3, ADLS, GCS, Delta Lake, Medallion Architecture ➡️ Data Transformation: dbt, SQL, Python, PySpark, Pandas, Power Query ➡️ Orchestration & Automation: Airflow, AWS Glue, Azure Data Factory, Cloud Dataflow ➡️ BI & Analytics: Power BI, Looker Studio, Excel, Google Sheets ➡️ Data Modeling: Kimball, Data Vault 2.0, Star Schema, Semantic Layers 𝐓𝐨𝐨𝐥𝐬 𝐈 𝐔𝐬𝐞: Power BI, Looker Studio, dbt, Python, SQL, PySpark, Airflow, AWS Glue, AWS DMS, Lambda, Redshift, Athena, BigQuery, Snowflake, Microsoft Fabric, Azure Data Factory, Synapse Analytics, Amazon S3, ADLS, GCS, GitAction, CI/CD. 𝐖𝐡𝐚𝐭 𝐘𝐨𝐮 𝐂𝐚𝐧 𝐄𝐱𝐩𝐞𝐜𝐭: ✅ Clean, automated data pipelines ✅ A reliable single source of truth ✅ Fast SQL and Python processing ✅ Dashboards that are clear, useful, and adopted by the business ✅ Strong data quality, testing, and documentation ✅ Clear communication and dependable delivery ✅ A complete BI package, not just another dashboard Whether you need a new pipeline, a scalable data warehouse, a lakehouse, a dbt project, a Power BI dashboard, or a full end-to-end analytics system, I can help you design it properly and deliver it with confidence. Send me a message with your current data challenge, and let’s discuss how to turn it into a reliable analytics solution.

I build the data infrastructure that makes LLMs actually work in production, RAG pipelines, vector search, and AI agents that don't hallucinate on your company's real data. Before AI, I spent 8 years as a Data Engineer building pipelines with [Python/SQL/Spark/Airflow/dbt, your actual stack]. That background is exactly why my AI systems don't fall apart at scale: I know how to move, clean, and structure data before an LLM ever touches it, which is where most "AI integrations" quietly fail. What I do: → Design and build RAG systems (retrieval-augmented generation) using Pinecone/Weaviate/pgvector/Chroma → Build production LLM pipelines with [LangChain/LlamaIndex/OpenAI API/Anthropic API] → Design embedding pipelines and vector databases that scale past prototype stage → Build AI agents and chatbots that connect to real business data, not toy demos → Handle the "boring" parts most AI freelancers skip: chunking strategy, latency, cost optimization, evaluation Recent results: ✅ "Cut RAG query latency by 60% on a 10M-vector index" ✅ "Built a support chatbot that reduced response time from 4 hrs to 90 seconds" ✅ "Migrated a client's AI prototype into a production pipeline handling 50K docs" I work best with: - Startups building their first AI product who need it to actually ship - Companies with an existing data stack who want to layer LLM capability on top - Teams whose "AI feature" broke in production and need someone who understands both data and models If your project involves LLMs touching real company data not just prompt-tweaking, let's talk. Send me your use case and current stack, and I'll tell you honestly whether RAG is even the right approach for it.

Full-Stack Data Consultant with extensive expertise in end-to-end data solutions, including data warehousing, ETL/ELT processes, and managing data infrastructure across all major cloud providers. I specialize in building robust data pipelines, modeling data for analysis, and creating actionable dashboards tailored to business needs. My experience also extends to machine learning, AI, and data analytics, providing clients with advanced insights to drive informed decision-making. Passionate about leveraging the latest industry trends and emerging technologies to drive innovation and improve business outcomes.

Turning messy data into decisions you can act on — Data Engineering, Reporting, Data Analytics, & Data Visualisation - 15+ years. I help companies stop guessing and start deciding with data. Over 15 years, I've built data pipelines, warehouses, and dashboards for teams at BCG, Netflix, Google, Pepsi, H&M, and Airbnb — cutting reporting time from days to minutes and surfacing insights that directly moved revenue and cost numbers. What I bring: 🔹 Top 0.01% Expert-Vetted talent on Upwork 🔹 500+ projects delivered, 20,000+ hours on Upwork, $500K+ earned — with a track record of long-term client relationships, not one-off gigs Where I add value: 🔹 Data Engineering & Pipelines — dbt, Airflow, Fivetran, Hevo Data, Python — building reliable, well-documented data models that your team can actually trust 🔹 SQL & Data Warehousing — PostgreSQL, MySQL, MSSQL, Oracle, Redshift, Snowflake, BigQuery, Azure — from schema design to query optimisation at scale 🔹 Dashboards & BI — Tableau, Power BI (DAX & Power Query), Looker, Looker Studio, QuickSight, Metabase, Superset, Grafana — dashboards built for decisions, not decoration 🔹 Reporting & Analytics — GA4, Shopify & e-commerce reporting, growth metrics, KPI frameworks, Retool, Domo, Airtable 🔹 Cloud — AWS, GCP, Azure I work best with teams who have a real business question — a cost that's too high, a metric that's unclear, a report that takes too long to build — and want it solved properly, not just patched. Send me your requirements, and let's figure out the fastest path to a clean, reliable answer.

MOST AI AND BI INITIATIVES FAIL because the underlying data foundation is broken. I am an Expert-Vetted Principal Architect (Top 1%) and 15x US Patent Holder who builds "Agentic" data foundations. I specialize in turning multi-source chaos into a Single Source of Truth that doesn't just report data, it reasons over it. My latest build, AgentMaestro, achieved 97% accuracy in the volatile Miami Real Estate market by replacing legacy "Black Box" ML with a "Two-Brain" Reasoning Architecture. I HELP AMBITIOUS ORGANIZATIONS SOLVE THREE CRITICAL PROBLEMS: 1. COST & LATENCY: I re-engineer legacy warehouses using Dataform and modern ELT logic to reduce cloud bills by 30%+ while achieving sub-2-second dashboard latency. 2. DATA INTEGRITY & ATTRIBUTION: I unify fragmented silos (Shopify, Meta, CRM, GTM/CAPI) into high-integrity Customer Data Platforms (CDP) to provide 100% visibility into ROI and Attribution. 3. REASONING-AS-A-SERVICE (RaaS): I move beyond simple "predictive modeling" into Agentic AI. I deploy LLM-driven reasoning engines (Vertex AI) that provide "Glass Box" audit trails for high-stakes decision-making. THE "MAESTRO" DIFFERENCE: I am not a "task-taker." I am a strategic partner who owns the entire data lifecycle. I design the proprietary logic that ensures your data is an asset, not a liability. Let's connect to architect your Single Source of Truth. CERTIFICATIONS - Google Cloud Professional Data Engineer - Google Cloud Professional Machine Learning Engineer - Google Data Analytics Professional - Google Business Intelligence Professional SKILLS Cloud Platforms: - Google Cloud Platform (GCP) Data Warehousing & Big Data: - BigQuery - BigLake - PostgreSQL - MySQL - SqlServer Data Modeling: - Dataform - dbt Machine Learning & AI: - BigQueryML - Vertex AI - TensorFlow - H2O - Caret - Scikit-learn - ML Model Development & Deployment Business Intelligence & Visualization: - Looker - Looker Studio - Google Sheets - Apache Superset - Airtable Programming Languages: - SQL - R - Python Data Engineering ELT & ETL: - Dataflow - Cloud Pub/Sub - Data Pipelines - Dataform - Cloud Functions. Ecommerce Platforms: - Shopify Data Science: - Predictive Analytics - Customer Segmentation - Data Mining - Statistical Analysis - RFM Analysis - Contribution Analysis - LTV - Time series forecasting - Recommender Systems

"𝗬𝗼𝘂𝗿 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗶𝘀 𝗼𝗻𝗹𝘆 𝗮𝘀 𝘂𝘀𝗲𝗳𝘂𝗹 𝗮𝘀 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗳𝗲𝗲𝗱𝗶𝗻𝗴 𝗶𝘁" Did you know that AI-Ready data quality can prevent 38% of reported AI project failures? All you need is 1 engineer who understands both AI and the data behind it to build reliable AI systems with clean data pipelines, secure integrations, and failure handling built in... I build production AI/ML and agentic applications. From LLM-powered automation to real-time speech-to-speech AI platforms backed by a strong data engineering foundation that most AI developers lack I help SaaS, AI Fintech and enterprise teams design reliable systems across the full path: data ingestion to warehouse to orchestration to ML-ready datasets to LLM/RAG workflows to automation and decision systems 𝗛𝗘𝗥𝗘'𝗦 𝗛𝗢𝗪 𝗜 𝗖𝗔𝗡 𝗛𝗘𝗟𝗣 𝗬𝗢𝗨... - Agentic AI & LLM Systems: I build LLM-powered applications and agentic workflows that automate business processes, connect to internal tools and work with real operational data. This includes RAG/GraphRAG systems, embeddings, vector search, prompt workflows, retrieval evaluation, FastAPI-based AI services, and reliable orchestration around LLM pipelines - RAG, GraphRAG & AI Knowledge Systems: I can help you build retrieval systems that are grounded in your documents, databases and business rules. My data engineering background helps me design better ingestion, chunking, metadata, data quality and retrieval pipelines so the AI layer has clean and trusted information to work with - AI Ready Data Engineering: Your AI system is only as good as the data behind it. I design and optimize production pipelines using Python, SQL, Snowflake, dbt, Apache Airflow, BigQuery, AWS, and modern ELT patterns. I focus on reliability, monitoring, data quality, incremental processing, and clean data models that can support analytics, ML, and AI applications - ML Pipelines & Automated Decision Systems: I have experience building analytics and ML-enabled systems such as anomaly detection, behavioral scoring, feature pipelines, fraud/risk insights and operational monitoring. I focus on practical ML and automation that business teams can trust, understand, and use in production - Data Platform Modernization: If your dashboards are slow, pipelines fail silently, KPIs do not match, or your team spends too much time reconciling data manually, I can help modernize the architecture. I have worked on cloud data platforms, warehouse design, dbt modeling, Airflow orchestration, and KPI frameworks that make reporting and AI use cases more reliable 𝗥𝗘𝗦𝗨𝗟𝗧𝗦 𝗜 𝗛𝗔𝗩𝗘 𝗗𝗘𝗟𝗜𝗩𝗘𝗥𝗘𝗗 - Reduced ETL runtime from 35 minutes to 7 minutes through pipeline and query optimization - Improved reporting latency from 24 hours to under 15 minutes with modern warehouse and ELT design - Improved pipeline reliability to 99.8% with orchestration, monitoring, retries, and validation - Increased BI adoption from 20 to 80+ users by standardizing metrics and improving reporting access - Supported analytics and ML use cases across fintech, SaaS, procurement, media, and enterprise environments - Built data foundations for AI-ready analytics, anomaly detection, and LLM-powered retrieval workflows 𝗛𝗢𝗪 𝗜 𝗪𝗢𝗥𝗞? I build proper custom AI and automation systems the same way I build production data platforms: reliable, documented, testable and designed for real users. I care about architecture, maintainability, monitoring, data quality, and business outcomes 𝗧𝗘𝗖𝗛 𝗦𝗧𝗔𝗖𝗞: AI/LLM: RAG, GraphRAG, LLM Integration, Embeddings, Vector Search, Prompt Workflows, Retrieval Evaluation Backend/API: Python, FastAPI, REST APIs, Async Workflows, Automation Services Data Engineering: Snowflake, Dbt, Apache Airflow, BigQuery, SQL, Python, ETL/ELT, Data Modeling Cloud/Infra: AWS, Docker, CI/CD, Monitoring, Production Deployment Patterns Analytics/ML: Anomaly Detection, Feature Engineering, ML-ready Datasets, BI, KPI Frameworks P.S. If you need someone who understands both; data layer and the intelligent AI layer on top of it, I would be happy to discuss your workflow and recommend the most practical production-ready approach