I am an analytical engineer with experience in data modeling and analysis from huge datasets. Whether you are trying to model the data for your company or analyze existing data, I can help! - I'm experienced in analytics languages; SQL, R, Python, Excel, and SPSS, and data modeling software DBT. - I'll manage projects from end to end with minimum supervision but ensure efficient communication for viable output.

Are you looking for an AI Engineer who can actually build, not just consult? I design and deploy end-to-end AI solutions: Voice AI agents, LLM-powered chatbots, RAG pipelines, AI automation workflows, and Generative AI applications. With 15+ years of experience across FMCG, healthcare, and enterprise tech, I bridge the gap between cutting-edge AI and real business outcomes. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🤖 WHAT I BUILD — AI & VOICE AI ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Voice AI Agents: inbound/outbound call bots using Vapi, Retell AI, and ElevenLabs for lead capture, appointment scheduling, and customer support automation ✅ AI Chatbots: custom LLM-powered bots (GPT-4, Claude, Gemini) with memory, context, and business logic ✅ RAG Systems: Retrieval-Augmented Generation pipelines using LangChain, LlamaIndex, and vector databases (Pinecone, Weaviate, ChromaDB) ✅ AI Automation: n8n, Make (Integromat), and Zapier workflows connecting AI to your CRM, ERP, and databases ✅ Agentic AI: multi-agent orchestration with LangGraph and AutoGen for complex task automation ✅ Prompt Engineering: structured system prompts, few-shot learning, and chain-of-thought frameworks ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 WHAT I BUILD: DATA & ANALYTICS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ✅ Business Intelligence: Power BI, Tableau dashboards with real-time data from multiple sources ✅ Data Engineering: data warehouses, ETL pipelines, data lakes on AWS, Azure, and GCP ✅ SQL & Python: advanced analytics, data modeling, and reporting automation ✅ CRM & ERP Integration: HubSpot, Salesforce, QuickBooks, SAP connected to your analytics stack ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏭 INDUSTRIES I KNOW DEEPLY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ FMCG | Healthcare | SaaS | Manufacturing | Financial Services I don't just hand over code: I bring domain knowledge. I understand the metrics that matter in your industry and build solutions that actually get used. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎓 BACKGROUND ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ▸ IIT Madras: Statistics (one of India's top technical institutions) ▸ B.Tech Computer Science: Kurukshetra University ▸ Former Data Analyst at Cisco Systems ▸ 100% Job Success Score on Upwork ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🛠️ TECH STACK ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ AI/LLM: OpenAI GPT-4o, Claude, Gemini, Llama, Mistral Voice AI: Vapi, Retell AI, ElevenLabs, Twilio Frameworks: LangChain, LlamaIndex, LangGraph, AutoGen Vector DBs: Pinecone, Weaviate, ChromaDB, FAISS Automation: n8n, Make, Zapier Data: Power BI, Tableau, Python, SQL, dbt Cloud: AWS, Azure, GCP Databases: PostgreSQL, MySQL, MSSQL, BigQuery, Snowflake ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💬 HOW I WORK ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ You bring the business problem. I handle everything from architecture to deployment. No jargon, no over-engineering, just solutions that work. → Clear communication and daily updates on active projects → Prototype-first approach so you see results fast → Full documentation and knowledge transfer on delivery Open to hourly engagements, fixed-price projects, and long-term retainers. Let's talk about what you're building.

I’m a CPA-credentialed Data Engineer and Data Scientist with 10+ years’ experience designing and scaling end-to-end data platforms, AI/ML workflows, and Power BI solutions for Fortune 100 and growing SMBs. I bridge deep technical expertise (Python, PySpark, SQL, Azure Data Factory, Microsoft Fabric, dbt) with a finance background to deliver reliable ETL pipelines, optimized data warehouses, predictive models, and interactive dashboards that drive strategic decision-making. Core Expertise Data Science & Machine Learning: Feature engineering, model training (classification, regression, survival analysis), deployed ML pipelines, probability calibration, threshold optimization, drift monitoring, SHAP explainability Data Engineering & ETL: Python/PySpark, SSIS, ADF, incremental loads, CDC, schema drift handling Cloud Data Platforms: Microsoft Fabric, Synapse Analytics, Azure SQL, AWS Redshift, S3 Database Design: Star/snowflake schemas, partitioning, indexing, performance tuning BI & Reporting: Power BI modeling (DAX, composite models, RLS), incremental refresh, paginated reports Automation & Integration: Power Automate, Power Apps, REST/API workflows Finance & FP&A: Financial data modeling, forecasting, reconciliation, audit trails Highlights Architected a Fabric Lakehouse and Spark pipelines to consolidate numerous financial sources accelerating month-end close by 40% Developed end-to-end ML pipelines for client reactivation and churn prediction models, including automated retraining and performance dashboards using SHAP explainability Led Big 4 FP&A platform redesigns, embedding governance, predictive analytics, and self-service BI across global teams Delivered turnkey BI and data engineering solutions for healthcare, retail, and professional services, including integrating clinical data for AI-driven insights Let’s connect to discuss how I can streamline your data architecture, implement AI/ML solutions, and empower your team with insights that scale.

I help growing companies turn messy operational data into reliable, analytics-ready infrastructure — and turn that data into insights teams actually use to make decisions. Over 5+ years, I've worked across the full data lifecycle for a logistics/SaaS company: building production pipelines, modeling data warehouses, optimizing databases, and delivering the reporting and analysis that came out the other end. Data Engineering Production ETL/ELT pipelines (batch and real-time/CDC) Data warehouse design & modeling (star/snowflake schema, SCD) Database optimization — query tuning, indexing, materialized views Orchestration (Airflow) and transformation (dbt) Automating manual/Excel-based reporting workflows Data Analysis & BI Exploratory analysis and ad hoc SQL reporting KPI frameworks and business metrics design Dashboard build-outs (Power BI, Apache Superset) Data cleaning, validation, and reconciliation Translating raw data into decisions — not just charts Tools I work in: Python, SQL, PostgreSQL, MySQL/MariaDB, MongoDB, BigQuery, ClickHouse, Databricks, PySpark, Apache Airflow, Apache NiFi, Debezium (CDC), dbt, Kafka, Power BI, Apache Superset. Where I add the most value: companies (10–500 employees) in SaaS, logistics, e-commerce, or fintech — whether you need someone to build the pipeline from scratch, fix a database that's buckling under real usage, or just make sense of the data you already have. Comfortable owning a project end-to-end, or plugging into a specific piece (a query, a dashboard, a pipeline fix) — happy to scope to what you actually need. Let's talk about what's slowing your data down.

Hi there — I’m Mohamed Elmougith, a Senior Data Management & BI Consultant with over a decade of experience helping organizations turn complex, scattered data into reliable, decision-ready insights. I specialize in Data Governance, Engineering, and Reporting, combining business understanding with technical execution across the full data lifecycle — from architecture and modeling to visualization and governance. 🔹 What I Do Best 🔵Design and build robust data architectures — Data Lakes, Warehouses, and Marts using Python, SQLModel, PostgreSQL, and SSIS / ADF. 🔵Develop ETL/ELT pipelines for ERP ecosystems such as SAP S/4HANA, Oracle EBS, and Maximo. 🔵Deliver insightful Power BI dashboards and performance-optimized DAX models for executive reporting. 🔵Implement data governance frameworks — policies, data quality monitoring, lineage tracking, and stewardship workflows using tools like OpenMetadata and custom Python automations. 🔵Advise leadership teams on Data Strategy & Operating Models, aligning technology with business objectives. 🔹 Beyond Consulting I’m also a Tutor-Reviewer at TripleTen, mentoring professionals in BI, analytics, and data architecture. 🔹 My Approach I work as a partner, not a vendor — helping clients design solutions that are maintainable, well-governed, and built for the long term. My goal is to make your data environment simpler, smarter, and more transparent. If you’re looking for a consultant who can bridge business strategy, data governance, and engineering execution, let’s connect.

Data Scientist & AI/ML Engineer with 5+ years in building systems that think, predict, and automate; not just API calls. I take raw, messy and unstructured data and turn it into production-ready pipelines, predictive models, and executive dashboards that drive decisions. I design and ship end-to-end data and ML systems: reducing time-to-insight from weeks to hours, automating workflows that used to take entire teams, and building models that directly feed revenue. If your business runs on data, I make it generate revenue, not just reports. 🔧 Core Expertise 1. Data Analytics & BI : Exploratory analysis, KPI frameworks, executive dashboards, A/B testing, cohort analysis (Excel, Power BI, Tableau, Plotly, Looker) 2. Data Science & ML : Predictive modeling, forecasting, statistical analysis, feature engineering, model validation and deployment (Scikit-Learn, PyTorch, TensorFlow, MLflow, AWS SageMaker) 3. Data Engineering : End-to-End pipelines, ETL/ELT automation, data warehousing, real-time and batch processing (Snowflake, Databricks, dbt, Apache Spark, Airflow) 4. Generative AI : RAG pipelines, LLM fine-tuning, agentic workflows, semantic search, prompt engineering, vector databases (LangChain, LlamaIndex, Pinecone, FAISS, OpenAI, HuggingFace) 5. Automation : Workflow orchestration, API integrations, intelligent agents, process automation, web scraping (n8n, Airflow, Lambda, Selenium, BeautifulSoup) 6. Cloud & Infrastructure model deployment, scalable data systems, serverless pipelines, storage and compute (AWS- SageMaker, EC2, S3, Lambda, RDS) 💡Why Clients Work With Me Most data projects fail not because of bad data, but because the person handling it understands models but not business. I bridge both. 5+ years solving real business problems with AI and data means I understand the business problem before I touch the data, and I build solutions that solve it end to end. I communicate at every step, flag issues before they become problems, and make sure what I build fits your workflow, your team, and your timeline. What you get is senior expertise, fast turnaround, and work that is built to last beyond the contract. Let's Talk If you have data that is not working hard enough for your business, that is exactly the problem I solve. Send me a message describing your project, and I will respond within an hour.

I help companies turn messy, fragmented data into reliable, analytics-ready datasets. My work spans the analytics engineering lifecycle: understanding business requirements, ingesting and transforming source data, designing dimensional models, implementing data-quality checks, and delivering trusted datasets for reporting and analytics. I bring 7+ years of experience working across data, analytics, and technology teams in financial services and global technology organizations. Unlike developers who focus only on the technical implementation, I can also work directly with business stakeholders to understand what the data needs to answer and translate those requirements into scalable data solutions. What I can help you build Analytics Engineering: SQL transformations and data pipelines dbt models, sources, tests, and documentation Staging, intermediate, and mart layers Fact and dimension models Star schemas and dimensional modeling Analytics-ready datasets Data Engineering & Quality: ETL/ELT pipeline development Python-based data ingestion and automation Data-quality testing and validation Pipeline troubleshooting and debugging Source-to-target mapping Data lineage and documentation Business Intelligence: Power BI semantic models and dashboards DAX measures and KPI development Reporting-layer optimization Migration from legacy BI environments Translating business requirements into data products Technology SQL | Python | dbt | PostgreSQL | Snowflake | Airflow | Power BI | AWS | Git | Docker ✔ Power BI Dashboard Development ✔ Data Modeling (Star Schema Design) ✔ DAX Measures & KPI Development ✔ Executive Reporting & Scorecards ✔ Qlik to Power BI Migrations ✔ SSRS to Power BI Migrations ✔ Power BI Performance Optimization ✔ Requirements Gathering & Documentation ✔ BI Strategy & Reporting Roadmaps ✔ Data Visualization Best Practices Industry Experience: Asset Management Financial Services Higher Education Nonprofits Enterprise Reporting & Analytics Digital Transformation Programs Whether you need a dashboard built from scratch, an existing Power BI solution optimized, or help translating business requirements into scalable reporting solutions, I can help. I combine technical development skills with business acumen to ensure analytics solutions are both technically sound and aligned to business goals.

I have several years of experience, using multiple programming languages and frameworks, in both academia and industry, in statistical modeling, probabilistic programming, classical machine learning and application of deep learning in several domains. The last several years I have been primarily ad cloud and data architect and data engineer and AI engineer. I have extensive experience in data modeling, pipeline development, data compliance, and worked with several database technologies (relational, NoSQL, graph, Hadoop and Spark), as well as CI/CD, API development, and architecting and development with multi-cloud computing platforms (Microsoft Azure, AWS, and GCP). I have deep experience in Databricks, and am a certified data engineer professional. 

I have worked in various fields such as, statistical genetics, behavior genetics, computational social science, app development, FinTech and healthcare data. The last 3 years I have run a consultancy while also building two profitable startups as data architect, data engineer while also being responsible for AI engineering and machine learning. Current Certifications: Databricks: Data Engineer Professional Azure: Developer, Data Scientist, Data Engineer, AI Engineer AWS: Data Engineer GCP: Data Engineer I have an extensive background in Python, R, JavaScript, SQL (T-SQL, PostgreSQL, SparkSQL, Databricks SQL, CQL, HiveQL, Cypher, KQL), with most data science libraries such as Pandas, NumPy, Scikit-learn, SciPy, SymPy, Rapids, PySpark, TensorFlow and TensorFlow Probability, Keras, PyTorch. I have extensive experience with standard data engineering tools: Snowflake, Databricks, Spark, PostgeSQL , dbt , Neo4j, Hadoop, Airflow, Beam, Iceberg, Hive, Kafka

, AirFlow, Flink, SuperBase, Hadoop, Dagster, Prefect, dot. As well as deep experience with several AI frameworks and automation tools: DSPy, LlamaIndex, BAML. LangChain, Hugging Face, AutoGen, LangGraph, a2a, MCP the AI frameworks of all 3 major cloud providers, n8n, Make, PipeDream, Flowise, Zapier, 5 Tran, and AirByte. 
I have extensive experience with multiple cloud providers, especially with the following skills and cloud products:
 General Cloud Development: Databricks in any cloud Azure: Storage, Networking, Functions, VMs, App Service, Synapse, Data Factory, DevOps, Kubernetes Service, API Management, Service Bus, Event Hubs, Event Grid, PubSub, Notification HubsRelay, IoT Hub, Power Apps, Power Automate, Azure Machine Learning, Synapse Analytics, Data Lake Storage, SQL Server, Cosmos DB, Data Flow, Stream Analytics, HDInsight, Redis, Cognitive Services, Text Analytics Service, LUIS, Custom Vision, Bot Service, Cognitive Search, and the general Power Platform AWS: S3, EBS, EC2, Lambda, Networking, RDS, Redshift, Arora, Athena, DynamoDB, DocumentDB, Lake Formation, Glue, Redis, SageMaker, Bedrock, Kinesis, QuickSight Elasstic Beanstalk, Elastic Kubernetes Service, Databricks, Pipeline, EMR, CloudWatch GCP: Storage, Networking, Cloud Functions, VMs, App Engine, Kubernetes Engine, API Gateway, BigQuery, BigTable, DataProc, Composer, DataFlow, Data Fusion, Data Studio, Cloud SQL, CloudSpanner, Cloud Memorystore, Pub/Sub

🥇 Top Rated Plus Data Architect & Engineer 🎯 Providing Decision Clarity via Automated Data Infrastructure Hi, I’m Farhan! Over the past three years, I’ve specialized in architecting data infrastructure and connected decision systems that give executives and business leaders a real-time, clear picture of their company’s performance, operations, and financials. During my tenure at Requin Analytics, I focused on engineering executive-level systems that integrated directly with company warehouses and cloud platforms—allowing leaders to track live logic through automated data pipelines. Having served global firms ZigTech Solutions, I’ve delivered results for founders and directors across E-commerce, SaaS, manufacturing, healthcare, logistics, and construction. As a Top Rated Plus Talent on Upwork, I focus on technical strategy for startups and growing enterprises, creating scalable architectures curated to match specific business growth goals and complex data requirements. 🥇 Here’s How I Can Help Your Business: 🎯 Decision Systems & Executive Intelligence • Executive & C-Suite Decision Systems • Automated Profit and Cash Flow Logic • Strategic KPI & Performance Architecture • E-commerce & Marketing Intelligence • Operational & Departmental Infrastructure • Custom-built systems based on your company’s unique requirements 🎯 Data Engineering & KPI Architecture • Automated data pipelines connected to cloud warehouses (BigQuery/Snowflake) • Centralized "Source of Truth" through dbt modeling and SQL optimization • Scalable KPI setups with accurate logic and high-speed performance • End-to-end data integration for better organizational visibility 🎯 Infrastructure Management & Strategy • Manage data roles, permissions, and security protocols • Optimize system performance and logic reliability 🛠 Tools I Work With Engineering: SQL, dbt, BigQuery, Snowflake, Power Query Intelligence: Power BI, Tableau Automation: Power Automate, Microsoft 365 Collaboration: ClickUp, SharePoint, Slack 🔍 How I Work 1️⃣ Discovery Call: I’ll discuss your business goals and the specific logic needed for your decision systems. 2️⃣ Architecture First: I’ll design the data flow and logic mapping before deployment, ensuring the system is built for scale. 3️⃣ Engineering & Collaboration: Frequent updates and feedback loops ensure the infrastructure matches your exact expectations. 4️⃣ Deliver Impact: The final systems are intuitive, automated, and built for executive-level clarity. Would love to schedule a short call to discuss how we can architect the data infrastructure that fits your business needs.

I help Masters/PhD students, academic researchers, and corporates turn messy data into publication-ready results, automated pipelines, and defensible insights — on time and with zero hand-holding.Bachelor’s-trained Applied Statistician (currently completing Master’s in Research Methods) with 10+ years delivering qualitative & quantitative analysis, systematic reviews & meta-analyses, statistical modeling, machine learning, and end-to-end data engineering. For students & researchers I deliver: 1. Full thesis/dissertation statistical support: data cleaning, power analysis, regression, survival, multilevel modeling, factor analysis, SEM in R, Stata, SPSS, or Python. 2. NVivo qualitative coding, thematic analysis, and mixed-methods integration. 3. Complete systematic reviews and meta-analyses (PRISMA-compliant, ready for journal submission — I recently delivered one in under 5 weeks). 4. Reproducible code + results sections that survive supervisor and reviewer scrutiny. For corporates I deliver: 1. Reliable data pipelines using dbt, Airbyte, Dagster, and Soda for automated ETL, quality monitoring, and scalable analytics. 2. Machine learning models (random forests, gradient boosting, clustering) and dashboards that actually drive decisions. My key tools are: R, Python, Stata, SPSS, Nvivo, Excel, dbt, Airbyte, Dagster, Soda, PowerBI