As a Data Scientist and analytics engineer, I specialize in building end-to-end, scalable data solutions that bridge the gap between raw data and actionable business strategy. I don't just build dashboards; I architect the robust pipelines and data models that power them. My expertise covers the full modern data stack, allowing me to streamline processes from ingestion to ETL. Whether you need to migrate legacy systems, orchestrate complex data flows, or design highly interactive visualizations, I can turn your data infrastructure into a reliable engine for growth. Core Competencies: Data Warehousing & Modeling: Snowflake, BigQuery, dbt, SQL Pipelines & Integration: Airbyte, Fivetran, Python, High Touch Analytics & Visualization: Tableau, Power BI, Hex, Retool, Looker Data Studio

👋 Hi, I’m a 🏆 ⭐️⭐️⭐️⭐️⭐️Top Rated Python Data Engineer & Data Visualization Expert at GroupBWT - a 100+ person data engineering company and official AWS, Snowflake & Databricks partner, building enterprise data systems since 2009. As a Python Big Data Engineer, I specialize in designing scalable data systems. My role as a Big Data Engineer is focused on building reliable pipelines, automation, and analytics infrastructure. Every Python Data Engineer decision I make is oriented toward scalability, performance, and data reliability. I work as a Big Data Engineer and Python Data Engineer on enterprise-grade systems where architecture matters for both ingestion and transformation layers. As a Data Engineer, I ensure that raw data becomes structured, usable, and ready for business intelligence. Here’s how I support our clients as a Python Big Data Engineer: ✅ Our ETL pipelines process over 100 million records monthly across major cloud data warehouses
 ✅ My solutions reduce manual reporting effort by up to 80% through end-to-end automation
 ✅ We build Python Data Engineer workflows for integrating and transforming complex datasets ✅ Every pipeline is tested and quality-checked to meet enterprise data standards 🔁 What I Do as a Python Azure Data Engineer and azure data engineer ⚙️ Data Engineering (Python AWS Data Engineer Core Work) 🔹 API & event-based ingestion using Python Data Engineer best practices 🔹 Python + SQL transformations 🔹 Data modeling, schema design, enrichment 🔹 ETL/ELT into Snowflake, Databricks, BigQuery with Python Data architecture 🔹 Monitoring, retries, observability & data quality testing for Python Data pipelines 🔹 CI/CD for pipelines & cloud cost optimization as a Python Data Engineer Platforms I’ve delivered as a Python Data Engineer process 100M+ records/month, integrate 30–80+ APIs, and power real-time BI environments. 📊 Data Visualization & BI (Python gcp Data Engineer Perspective) 🔹 I bridge raw data with business decisions as a Python gcp Data Engineer 🔹 Power BI, Looker Studio & Tableau dashboards connected by Python GCP Data Engineer pipelines 🔹 Executive KPI reporting built by a Python AWS Data Engineer 🔹 Semantic layer & metric standardization in Python Data Engineer systems 🔹 Real-time reporting (<5 min latency) enabled by Python Data Engineer architecture 🔹 BI performance optimization from a Python Data Engineer point of view 🔹 Data storytelling for leadership & operations powered by Python Data Engineer workflows My solutions as a Python Data Engineer reduce manual reporting effort by up to 70-80% and significantly improve forecasting accuracy. 🧩 Recent Experience (Python Data Engineer and Machine Learning Projects) 🔹 Retail & eCommerce Data Warehousing (Python Data Engineer) Built ingestion + normalization pipelines for 120+ eCommerce sources, syncing ~500K SKUs/day into Snowflake / BigQuery using Python Data Engineer architecture. 🔹 FinTech Ingestion & Reporting Layer (Python Data Engineer ) Delivered automated pipeline pulling from 30+ sources (APIs, DBs, files), built with Python Data Engineer logic for validation, transformation, and reporting. 🔹 Government ETL & Document Processing (Python Azure Data Engineer | Data Analyst) Automated processing of 10K+ documents/day using Python Azure Data Engineer workflows and Machine Learning: extraction, classification, mapping, and database loading. 🔹 Healthcare Data Normalization & Compliance (Python AWS Data Engineer | Data Analyst) Cleaned millions of records using Python AWS Data Engineer pipelines with Machine Learning, schema mapping, PII-aware handling, and reproducible transformations. 🔹 Large-scale Cloud Migrations (Python Data Engineer | Data Analyst) Migrated legacy systems into BigQuery/Snowflake using Python Data Engineer architecture with Machine Learning, incremental loads and automated pipelines. 💻 Tech Stack (Python Data Engineer | Data Analyst Toolkit) ⚙️Languages: Python, SQL, DAX, Power Query, PySpark, Scala, Bash/Shell, JavaScript, etc.
 ⚙️Data Engineering & Processing: PySpark, dbt, Airflow, Prefect, CDC, REST & GraphQL, etc.
 ⚙️Data Warehouses & Databases: Snowflake, Databricks, BigQuery, AWS, PostgreSQL, MSSQL
 ⚙️Cloud Platforms: AWS: S3, Glue, Lambda, CloudWatch, Athena, Redshift, BigQuery, Dataflow
 ⚙️Data Modeling & Architecture: Star schema, Snowflake schema, Lakehouse architecture, etc.
 ⚙️Monitoring & Data Quality: dbt, Prometheus, Grafana, AWS CloudWatch, GCP Monitoring, etc.
 ⚙️BI & Visualization: Power BI (Desktop, Service), Tableau, Looker Studio, Metabase, etc.
 ⚙️DevOps & CI/CD: Git, GitHub, GitLab CI, Docker, Terraform, etc. 🚀 If you need automated pipelines, clean data models, and executive-level dashboards - as a Python Data Engineer and Data Analyst I can help you build a robust system from end to end. ➡️ Invite me to your job and let’s design a scalable data strategy with a Python Data Engineer leading the way. Last updated June 15, 2025

I help organizations transform fragmented, siloed data into scalable, high-performance cloud data platforms that support clear reporting and better decision making. My focus is on building systems that are structured, scalable, and designed to support long-term growth. With 6+ years of experience across AWS, Google Cloud, and Azure, I design and implement end-to-end data solutions, from ingestion and transformation to warehouse modeling, analytics, and AI-driven insights. I do not just build pipelines. I architect resilient, scalable systems designed for growth, performance, and long-term business impact. 𝐖𝐡𝐚𝐭 𝐈 𝐝𝐨: ✅Design and deploy AWS serverless solutions using Lambda, API Gateway, DynamoDB, S3, and VPCs ✅Build robust ETL pipelines with AWS Glue, Redshift, Kinesis Firehose, and Snowflake ✅Unified analytics platforms (Shopify, Salesforce, HubSpot, Notion, IoT, Marketing APIs) ✅AI-driven data systems including RAG architectures, natural language to SQL solutions, LangChain and OpenAI integrations, vector databases such as FAISS, Chroma, and Qdrant, and AI-powered analytics applications. ✅Develop CI/CD pipelines with CodePipeline, CodeBuild, Jenkins, automating deployment and testing ✅Implement real-time streaming solutions using Apache Kafka and Google Pub/Sub ✅Optimize database performance with MySQL, MongoDB, RDS, and ElasticCache ✅Ensure cloud security and monitoring with IAM, CloudWatch, Trusted Advisor, and Elasticsearch 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐒𝐤𝐢𝐥𝐥𝐬: 🔹Languages & Scripting: Python, Node.js, JavaScript, Bash/Shell 🔹Cloud: AWS, GCP, Azure 🔹DevOps & Automation: CodeBuild, CodePipeline, Jenkins, CI/CD 🔹AI: LangChain, OpenAI API, Vector Databases 🔹Streaming: Kafka, Kinesis, Pub Sub 🔹Data Warehousing & Analytics: Snowflake, Redshift, BigQuery, Synapse 🔹Operating Systems: RHEL, Ubuntu Linux 🔹Orchestration: Airflow, dbt 🔹Infrastructure as Code: Terraform Whether you need data pipelines, BI dashboards, serverless apps, or ETL optimization, I deliver clean, maintainable, and high-performing solutions tailored to your business goals. 👉 Ready to make your data work harder for your business? 𝐋𝐞𝐭’𝐬 𝐜𝐨𝐧𝐧𝐞𝐜𝐭 and build something smart together.

Most companies don’t have a data technology problem. They have a data strategy, architecture, and execution problem. Your CRM, ERP, application databases, financial systems, marketing platforms, and operational tools contain valuable data—but they don’t work together. Reporting is slow, KPIs aren’t trusted, and leadership wants to use AI but isn’t sure whether the underlying data is ready. That’s where I help. My name is Franck Leveneur. 𝗜 𝗯𝗿𝗶𝗻𝗴 𝟯𝟬+ 𝘆𝗲𝗮𝗿𝘀 𝗼𝗳 𝗵𝗮𝗻𝗱𝘀-𝗼𝗻 𝗱𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗲𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲. Since 2018, I've taught Data Management at the UCLA Anderson School of Management for the Master of Science in Business Analytics (MSBA) program. I founded Data-Sleek in 2020 as a boutique consulting firm built around this exact gap in the market. On Upwork, we've earned over $𝟓𝟎𝟎,𝟎𝟎𝟎 𝐚𝐜𝐫𝐨𝐬𝐬 𝟏𝟑𝟗 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝 𝐣𝐨𝐛𝐬. Clients consistently tag my work as "Committed to Quality," "Solution Oriented," and "Clear Communicator." When you work with me, you're not getting a junior freelancer learning on your dime; you're getting a 𝐛𝐚𝐭𝐭𝐥𝐞-𝐭𝐞𝐬𝐭𝐞𝐝 𝐯𝐞𝐭𝐞𝐫𝐚𝐧 who has built data ecosystems for high-growth companies like Numerade, Digital Asset Research, and Johns Hopkins, among 15+ others. ──────── 🚨𝐓𝐇𝐄 𝐏𝐑𝐎𝐁𝐋𝐄𝐌 𝐖𝐄 𝐒𝐎𝐋𝐕𝐄 Your company has data - a lot of it. But: 1. Your systems don't talk to each other (ERP, CRM, EHR, TMS - all siloed) or you don’t know where to start Comment end 2. KPI reporting takes too long, and nobody quite trusts the numbers 3. You want to use AI and predictive analytics, but your data isn't ready 4. You've tried BI tools. You still don't have real answers. This is not a tool problem. It's a foundation problem. And that's exactly what we fix. 🚀 𝐇𝐎𝐖 𝐖𝐄 𝐖𝐎𝐑𝐊 - 𝐓𝐇𝐄 𝐅𝐎𝐔𝐑-𝐏𝐈𝐋𝐋𝐀𝐑 𝐅𝐑𝐀𝐌𝐄𝐖𝐎𝐑𝐊 We guide clients through a structured data journey. You can engage at any stage: 1. Data Strategy (Discovery & Alignment, optional but recommended) Data inventories, AI readiness assessments, architecture design, and strategic roadmaps. 2. Data Centralization (Integration & Governance) Single source of truth via Snowflake, BigQuery, or Redshift connected through Fivetran and governed pipelines. 3. Data Transformation (Modeling & Preparation) dbt consulting, semantic layers, and ETL/ELT pipelines that model your data for analysts and AI. 4. Data Activation (Insights, Prediction & AI) BI, Tableau dashboards, predictive analytics, and ML wherein raw data turned into real business outcomes. DATA WAREHOUSE CONSULTING SERVICES Struggling with complex data warehousing projects can hinder your company’s ability to scale. Our data warehouse consulting services are tailored to address your business’s data needs. 🙅🏼‍♂️ 𝐃𝐀𝐓𝐀𝐁𝐀𝐒𝐄 𝐄𝐗𝐏𝐄𝐑𝐓𝐈𝐒𝐄 - 𝐓𝐇𝐄 𝐓𝐇𝐈𝐍𝐆 𝐌𝐎𝐒𝐓 𝐂𝐎𝐍𝐒𝐔𝐋𝐓𝐀𝐍𝐂𝐈𝐄𝐒 𝐂𝐀𝐍'𝐓 𝐃𝐎 Unlike modern data stack consultancies that only know cloud tools, we know how the underlying transactional systems actually work. I have 15+ years as a Senior MySQL DBA and deep expertise across: ➝ MySQL & AWS Aurora ➝ PostgreSQL ➝ ClickHouse ➝ MS SQL Server ➝ SingleStore Performance tuning, partitioning, replication, and scaling, not just dashboards on top of messy data. 🏭 𝐈𝐍𝐃𝐔𝐒𝐓𝐑𝐈𝐄𝐒 𝐖𝐄 𝐒𝐏𝐄𝐂𝐈𝐀𝐋𝐈𝐙𝐄 𝐈𝐍 ➔ Construction ➔ Healthcare ➔ Higher Education ➔ Insurance ➔ Transportation ➔ SaaS ➔ EdTech ➔ FinTech We have dedicated playbooks, industry-specific data models, and named case studies in each. If your company is in one of these five, we've already solved your problem before. 💯 𝐏𝐑𝐎𝐕𝐄𝐍 𝐑𝐄𝐒𝐔𝐋𝐓𝐒 🏆 Johns Hopkins (Higher Education): Data warehouse architecture consulting reduced reporting time by 40% and increased data accuracy by 35% within the first year. 🏆 Numerade (EdTech): Redesigned database schema and ETL processes - query times dropped from several minutes to sub-second, system outages eliminated, scaled to unlimited concurrent users, subscriber growth followed. 🏆 Digital Asset Research (FinTech/Crypto): Built a real-time ingestion pipeline handling 40 million rows daily (250M+ trades). Client expanded their client base by 600% and captured the largest market share in their category. 💡 𝐀𝐈 𝐑𝐄𝐀𝐃𝐈𝐍𝐄𝐒𝐒 𝐀𝐒𝐒𝐄𝐒𝐒𝐌𝐄𝐍𝐓 - 𝐓𝐇𝐄 𝐑𝐈𝐆𝐇𝐓 𝐖𝐀𝐘 𝐓𝐎 𝐒𝐓𝐀𝐑𝐓 𝐀𝐈 Most AI projects fail because the data foundation underneath them isn't ready; not because AI is hard. If you want predictive analytics, ML models, or intelligent automation, start here: → Fixed-fee engagement · 4-6 weeks · Clear deliverable: which AI use cases your data can support today, and the roadmap to support more. ──────── 🌱 𝐋𝐄𝐓'𝐒 𝐆𝐄𝐓 𝐒𝐓𝐀𝐑𝐓𝐄𝐃 We always start with a free initial consultation to scope the work properly before any engagement begins. Send a message - let's see if we're a fit!

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.

Fractional CDO and Senior Data Engineer for Series A-B SaaS, marketplaces, and consumer-tech. Builds full-stack data platforms end-to-end: warehouse (Snowflake, BigQuery, ClickHouse), transformation (dbt, Fivetran), BI (Power BI, Looker). 56 Upwork contracts closed, 5+ ongoing 1-3 year retainers including Tools for Humanity (Worldcoin), BHL, and OpenTag. Service menu: • Data strategy and roadmap (from Series-A "we need data" to Fortune-100 architecture) • Warehouse stand-up on Snowflake, BigQuery, or ClickHouse — from scratch or migration • Modern data stack: dbt models, Fivetran ingestion, Airflow orchestration, semantic layer • BI implementation and audit (Power BI, Tableau, Looker, Looker Studio, Metabase, Superset) • Analytics team hiring, mentoring, KPI stewardship, data governance • Customer Data Platform and event tracking (GA4, server-side GTM, attribution) Recent engagements and rates: • ClickHouse Expert, $176/hr, 7 months. 12B rows/month, query p95 14s to 380ms. • Data Consultant CDO, $120/hr, 8 months. Built the data org from scratch for a Series B fintech. • Database and Cloud Architecture Consultant, $125/hr. • Looker Studio migration, $115/hr. 40 Sheets dashboards migrated, weekly reporting time cut 70%. • Long-term retainers: OpenTag Superset ($90/hr, 13 months), BHL Metabase ($80/hr, 13 months), Tools for Humanity Worldcoin ($75/hr, 2.5+ years). Where I fit best: • You have raw data in production but no unified view for the team • Your BI is fragmented across Sheets, Excel, and three half-built dashboards • Your gap is senior architecture, and hiring more junior engineers won't close it • You want a decision partner who thinks in unit economics Where I don't fit: • Pure ML/CV/NLP research (LLM + RAG for data pipelines is fine) • Marketing/CRO tracking without an analytics stack under it • Junior data-entry or dashboard-copy tasks Communication: async-first, Slack + Loom + written docs. CET timezone, US-friendly hours daily. Send a message with your stack, one business question, and the number you want to move. Reply within 8 hours business days.

Senior Data Engineer and AI Engineer with 15+ years in data engineering, AI engineering, and cloud data platforms. I build production data pipelines, ETL workflows, LLM and RAG systems, and machine learning infrastructure on AWS, GCP, Azure, Snowflake, Databricks, and Apache Spark. Most of my data engineering work is end to end. I take a messy data problem, or an AI feature that "almost works," and turn it into something reliable that runs in production without someone babysitting it. After 15+ years as a data engineer, you learn the hard part is rarely the model or the framework. It's the data, the edge cases, the pipelines, and keeping the system maintainable once you've handed it over. As an AI engineer I treat LLM and RAG work the same way: take a prototype that almost holds together and make it a production AI system that survives real traffic, real users, and real data. Recent data engineering and AI engineering projects: - An AI inbound phone system built on Twilio with OpenAI Whisper and GPT-4, handling real-time voice intake and call routing. - Enterprise Power BI data models for healthcare and financial reporting, around 30 tables and 40+ DAX measures, including IFRS 9 staging, RAROC, and NIM trends. - HL7 FHIR R4 integrations with Epic, Cerner, and Athenahealth for a clinical AI platform. - Cut LLM inference cost on a high-volume voice product by 25% by reworking how it used the OpenAI Realtime API and its per-turn token replay. Data engineering: Apache Spark, PySpark, dbt, Apache Airflow, ETL and ELT pipelines, data warehousing, data modeling, Snowflake, BigQuery, Redshift, Databricks, Delta Lake, Kafka, Kinesis, Fivetran. AI engineering and machine learning: OpenAI GPT-4o, Claude, Gemini, LangChain, LlamaIndex, RAG pipelines, AI agents, prompt engineering, vector search (Pinecone, Weaviate, pgvector), PyTorch, TensorFlow, scikit-learn, MLflow, model deployment. Cloud and DevOps: AWS (Glue, EMR, Lambda, Redshift, SageMaker, Athena), GCP (BigQuery, Dataflow, Vertex AI), Azure (Synapse, Data Factory, Azure ML), Terraform, Docker, Kubernetes, GitHub Actions. Automation and integration: n8n, Make, Power Automate, REST and GraphQL APIs. Governance and compliance: GDPR, HIPAA, SOC 2, RBAC, PII masking, encryption, data lineage. Languages: Python, SQL, Scala, PySpark, FastAPI, Flask. How I work: I'd rather ask the right questions up front than build the wrong thing quickly. I'll tell you when something is a bad idea, give you timelines I can keep, and leave you with code and documentation your own team can maintain. I've delivered data engineering and AI engineering projects for startups and enterprises across the US, Europe, and Asia. If you're looking to hire a data engineer or AI engineer who can own the work end to end, from raw data pipeline to production AI system, I'm available now. Tell me what you're building and I'll give you a straight answer on how I'd approach it.

I build data pipelines and dashboards that help companies actually use their data. Over the past 5 years, I've helped 70+ clients — from early-stage startups to enterprise teams — set up analytics infrastructure, migrate to modern data stacks, and create dashboards their teams actually use daily. What I do best: BI & Dashboards — Looker, Looker Studio, Tableau, Power BI, Mode. I've built executive dashboards, marketing attribution reports, and customer analytics views for SaaS, e-commerce, and gaming companies. Data Pipelines & ETL — BigQuery, Snowflake, dbt, Airbyte, Fivetran. I design and build pipelines that are reliable, documented, and maintainable — not spaghetti SQL that breaks when you're on vacation. Analytics Engineering — GA4 setup, event tracking, data modeling, KPI frameworks. I help teams go from "we have data somewhere" to "we make decisions with data." Recent wins: Built a GA4 + Looker Studio analytics stack for a German startup (troubleshooting complex attribution issues) Developed dbt models powering customer dashboards in Amazon QuickSight Created AI chatbot POC processing analytical datasets — delivered in weeks, not months I'm responsive, I document my work, and I don't disappear mid-project. Let's talk about what you're trying to build.

𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 & 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 | 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜, 𝗦𝗤𝗟, 𝗣𝘆𝘁𝗵𝗼𝗻 & 𝗘𝗧𝗟 I help businesses turn raw, scattered data into reliable data pipelines, automated reports, and interactive Business Intelligence dashboards that support faster, data-driven decisions. If you're dealing with manual reporting, disconnected data sources, slow ETL processes, or dashboards that don't provide actionable insights, I can help. 😫 𝗖𝗵𝗮𝗹𝗹𝗲𝗻𝗴𝗲𝘀 𝗜 𝗦𝗼𝗹𝘃𝗲 • Manual and repetitive reporting • Data from multiple disconnected sources • Complex or inefficient ETL pipelines • Poor data quality and inconsistent reporting • Dashboards that don't provide actionable insights • Time-consuming data preparation and analysis 💡 𝗪𝗵𝗮𝘁 𝗜 𝗗𝗼 As a Data Analyst and Data Engineer, I design and build data solutions that connect, transform, analyze, and visualize your business data. 𝗖𝗼𝗿𝗲 𝗦𝗲𝗿𝘃𝗶𝗰𝗲𝘀: • Power BI Dashboard Development & Data Visualization • Business Intelligence (BI) Dashboards • Data Analytics & KPI Reporting • SQL Data Analysis & Database Queries • Python Data Analysis & Automation • ETL Development & Data Transformation • Data Engineering & Data Pipelines • Automated Reporting & Reporting Workflows • API & Data Source Integrations • Looker Studio & Tableau Dashboards • Executive & Management Dashboards 🛠 𝗧𝗼𝗼𝗹𝘀 & 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀 Power BI | SQL | Python | ETL | Data Engineering | Data Analytics | Business Intelligence | Looker Studio | Tableau | APIs | Data Visualization ⭐ 𝗪𝗵𝘆 𝗪𝗼𝗿𝗸 𝗪𝗶𝘁𝗵 𝗠𝗲? ✔ Clean and reliable data pipelines ✔ Automated and scalable reporting solutions ✔ Interactive, business-focused dashboards ✔ Clear KPI and performance reporting ✔ Solutions designed around your actual business needs 𝗥𝗲𝘀𝘂𝗹𝘁𝘀 𝗜 𝗖𝗮𝗻 𝗛𝗲𝗹𝗽 𝗬𝗼𝘂 𝗔𝗰𝗵𝗶𝗲𝘃𝗲 • Reduce manual reporting work • Connect and consolidate multiple data sources • Automate data preparation and reporting • Improve data visibility and reporting accuracy • Turn complex data into actionable business insights 📩 𝗟𝗲𝘁'𝘀 𝗧𝗮𝗹𝗸 Have a Power BI, Data Analytics, Data Engineering, ETL, SQL, Python, or Business Intelligence project? Send me the details, and let's discuss how I can turn your data into a reliable reporting and decision-making solution.

👋 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.