Passionate, and detail-oriented Analytics Engineer with a strong focus on bridging the gap between data engineering and business analytics to empower self-service analytics and drive informed decision-making. Committed to continuous improvement though experiences and always eager to take on new challenges that make a real impact. Self Initiated Projects ✅ Core Banking Data Mart Automation - dbt | Airflow | PostgreSQL 🔗 ▶ Designed and implemented an end-to-end ATM Withdrawal Transaction Data Mart using dbt (Bronze–Silver–Gold layers) on PostgreSQL, incorporating incremental models, data quality tests, and freshness checks. ▶ Orchestrated automated 10-minute incremental updates using Apache Airflow, enabling nearly real-time data availability for downstream analytics. ✅ Core Banking System – ATM Withdrawal Streaming Simulation - Databricks | PySpark | Delta Lake | Streaming ETL ▶Designed and implemented a core banking data model, including 6 reference tables, 5 entity tables, and a double-entry financial journal table to simulate ATM cash withdrawal operations. ▶Developed a high-volume synthetic data generator and real-time PySpark Structured Streaming pipeline in Databricks to simulate and transform 100,000+ double-entry ATM transactions per minute into a unified Silver-layer data mart using Delta Lake, stream-stream joins, watermarks, and broadcast joins. ✅Real-Time Change Data Capture (CDC) Pipeline with Kafka, Debezium, and ClickHouse ▶Built a real-time data pipeline by setting up Kafka with Confluent Control Center and developing a Python Faker script to generate and stream 10M synthetic financial records. ▶Simulated a production system by sinking data into PostgreSQL, then enabled CDC with Debezium, replicating changes in real time to a ClickHouse target database with a custom-designed schema. ✅ Data Transformation with DBT ▶Built staging schemas and incremental models with well-defined schema documentation to enable efficient, modular data transformation, and ensure maintainability. ▶Developed custom macros to standardize logic and reduce code duplication and snapshots to manage slow-changing dimensions ✅ Technical Expertise: ▶ Languages & Platforms: Python, SQL; Microsoft Azure, Visual Code Studio, Jupyter Notebook, DBreaver, Docker ▶ Databases and Tools: Oracle, Postgre SQL, MySQL, ClickHouse ▶ Big Data Technologies: Apache Kafka, Airbyte, PySpark, dbt, Apache Airflow, Databricks ▶ Data Visualization: Tableau, Power BI, Metabase, Superset ▶ Microsoft: Advance Excel ▶ Soft Skills: Stakeholder Management, Time Management, Work Prioritization, Leadership ✅ Areas of Expertise : ▶ Data Architecture & Pipeline Engineering Proficient in designing and implementing real-time data pipelines, including CDC- enabled architectures, with a strong focus on scalable ETL/ELT processes and robust data modeling within modern data warehouse frameworks such as Medallion Architecture ▶Advanced SQL & Data Transformation Complex transformation logic using SQL, dbt, and custom macros to standardize logic across models ▶ Dashboard & Report Automation Create interactive dashboards in Tableau, Metabase, and Power BI supporting business units from sales to operations. ▶ FinTech Transaction analysis Customer analysis - Customer Lifetime Management, Campaign Analysis, Customer Cohort Development, Churn & Retention Analysis ▶ Inventory & Supply Chain Analytics Demand planning, Replenishment Model, Out of Stock analysis & Lost Sales, Safety Stock, Inventory Aging, Turnover, Product segmentation Industries I have worked for: FMCG, E-Commerce, FinTech(Mobile Financial Service)

✅ 4x Microsoft Certified (PL-300, AI-900, DP-900, MS-900) | 100% Job Success | Top Rated From Wall Street analytics to AI-powered dashboards. I build BI systems that C-suite executives trust to make decisions. With an Economics degree, a Systems Engineering degree, and experience at Morgan Stanley and Moody's Analytics, I bring a rare combination: I understand both the financial logic behind the numbers and the engineering required to deliver them reliably at scale. I also led M&A analytics at Kareo (healthcare SaaS) and founded Ceteryx, a data intelligence consultancy. 𝗪𝗵𝗮𝘁 𝗜 𝗗𝗲𝗹𝗶𝘃𝗲𝗿 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗗𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱𝘀 & 𝗥𝗲𝗽𝗼𝗿𝘁𝗶𝗻𝗴: Executive KPI scorecards, financial reporting suites, operational dashboards, designed for CFOs, COOs, and board presentations. 𝗣𝗼𝘄𝗲𝗿 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: Power Apps for data capture + Power Automate for workflow automation + Power BI for live reporting, a fully integrated Microsoft stack. 𝗔𝗜-𝗘𝗻𝗵𝗮𝗻𝗰𝗲𝗱 𝗕𝗜 𝗦𝗼𝗹𝘂𝘁𝗶𝗼𝗻𝘀: I integrate OpenAI/Claude into Power Platform workflows, automated executive summaries, anomaly detection, and natural-language data queries. 𝗖𝗥𝗠/𝗘𝗥𝗣 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻𝘀: Salesforce, HubSpot, Dynamics 365, NetSuite, QuickBooks. I connect your operational systems to Power BI for a single source of truth. 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴: ETL pipelines (Python, Airflow, dbt), data modeling, Snowflake/PostgreSQL/Azure optimization. 𝗣𝗿𝗼𝘃𝗲𝗻 𝗜𝗺𝗽𝗮𝗰𝘁 Reduced ETL runtime 70% for a NASDAQ SaaS firm → $30K/mo in compute savings Built real-time fraud detection pipeline (99.3% accuracy) with Python & Kafka Migrated 50+ on-prem SQL databases to AWS with zero downtime Delivered CFO-grade SaaS metrics dashboards (MRR, LTV, churn) for board presentations 𝗪𝗵𝘆 𝗠𝗲 Ex-Morgan Stanley & Moody's Analytics: I speak finance fluently 4x Microsoft Certified: PL-300, AI-900, DP-900, MS-900 Founder of Ceteryx: entrepreneurial mindset, ownership mentality Fluent in English, Spanish, Italian Fast starts: most clients see first results in < 7 days Free 30-minute consultation to scope your project ⭐ Client Reviews "Built a dynamic, CFO-grade dashboard from minimal specs. Hit every deadline." "Joined disjointed data I thought impossible and delivered CXO-ready insights." "Responsive, insightful, knows the ins and outs of MS Power Platforms and OpenAI integration." 📞 Send me your data challenge: I'll blueprint a solution in 24 hours, no strings attached.

I'm a freelance data engineer/analyst with a background in martech and industrial start-ups. Through my experiences, I've developed the ability to quickly comprehend complex businesses and drive positive outcomes. Thriving in fast-paced and innovative environments, I lead data projects that directly contribute to business success. I can help you achieve many data projects such as : - data platforms migrations - database design - data pipeline building - impactful dashboard building From a technical standpoint, I'm proficient in : - ETL tools : DBT, Matillion - Dataviz tools : Redash, Preset, and Power BI - SQL : Snowflake, Postgre, AWS, BigQuery - Python Let's collaborate to drive innovation and achieve results.

Most data pipelines don't fail loudly. They rot quietly. A job starts silently skipping rows. A dashboard still loads, but the numbers stopped matching reality weeks ago. The warehouse bill creeps up because nobody ever tuned the queries. Eventually someone exports to a spreadsheet "just to be sure" and that's the moment the system stopped being trusted. That's the work I do: build data pipelines and warehouses people actually rely on, and fix the ones that quietly stopped working. Over the last 3 years I've delivered 55+ data projects across finance, healthcare, energy, and e-commerce, from one-off ETL jobs to platforms processing billions of records a day. I work GCP-first (BigQuery, Airflow, dbt, Dataflow), and I'm comfortable across AWS, Postgres, and the messy real-world stack most teams actually have. What I build: - End-to-end ETL/ELT pipelines in Python, SQL, Airflow, and dbt - BigQuery / Snowflake / Redshift warehouses and data models that stay clean as they grow - Migrations off legacy jobs and on-prem databases — without losing data in the move - Metabase, Looker Studio, and Power BI dashboards your team will actually open - Query and cost optimization when your warehouse bill stops making sense - API integrations with proper logging, retries, and checkpoints, so failures are visible instead of silent You probably need me if: - Your pipelines break and you hear it from a stakeholder, not an alert - Reports run slow, cost too much, or quietly disagree with each other - A previous developer left and nobody fully understands the setup anymore - You're scaling fast and the current data stack is starting to crack A few real results: - Architected pipelines processing 5B+ records daily at 99% reliability - Cut a client's warehouse costs ~50% by migrating legacy jobs to BigQuery - 4× throughput and 70% faster ingestion on an API pipeline pulling 2K+ domains a day - 40% faster pipeline runs through Airflow optimization How I work: a clear yes/no on feasibility before you commit, regular updates, and no disappearing mid-project. Most clients come back — usually because fixing one thing surfaces the next. If that sounds like your situation, send a short note on what's breaking or what you're trying to build, and I'll tell you straight what it'll take.

Analytics Engineer & BI Developer | 10+ years of experience building scalable analytics solutions using Looker, Tableau, SQL, BigQuery, and modern analytics & AI-assisted reporting workflows. ⭐ 100% Job Success Score · 34 Projects · 1,100+ Hours Delivered I help businesses transform complex data into scalable dashboards, automated reporting systems, and modern analytics solutions that support faster and smarter decision-making. I have worked across Retail, SaaS, and enterprise analytics projects involving: ✔ Looker / LookML Development ✔ Tableau Dashboards & BI Reporting ✔ BigQuery & Advanced SQL ✔ Analytics Engineering & Data Modeling ✔ KPI & Executive Reporting ✔ Dashboard Performance Optimization ✔ ETL & Automated Reporting Pipelines ✔ AI-Assisted Analytics & Gen AI Workflows ✔ Dashboard Migrations (Qlik · Tableau · Looker) Tools: Looker · LookML · Tableau · Power BI · Looker Studio · BigQuery · SQL · GCP · Grafana · Excel · Google Sheets Recently built AI-assisted analytics workflows and conversational reporting experiences that allow non-technical teams to explore and query business data without writing a single line of SQL. I build scalable, business-friendly analytics systems - not just dashboards.

I am a Senior Data Engineer & Data Analyst with over 7 years of hands-on experience across SQL Databases, Data Engineering, ETL Pipelines, Cloud environments, Data Analytics and Data Warehousing. I deliver end-to-end data solutions, seamlessly bridging the gap between backend ETL Pipelines and frontend business insights to help companies make faster, better decisions. WHAT CAN I DO FOR YOU: • Build ETL and ELT pipelines to centralize fragmented business data. • Design data warehouses and dimensional models (star and snowflake). • Optimize complex SQL queries and improve database performance using standard data optimization techniques. • Develop interactive, automated dashboards and reporting suites for business stakeholders using Power BI, MicroStrategy, Superset, and Qlik. • Implement cloud data solutions using the Microsoft Azure ecosystem (Data Factory, Synapse, Fabric, Data Lake). • Clean, structure, format, and prepare massive, messy datasets for deep data analytics. TECHNICAL STACK: • Cloud & Warehouses: Azure (Data Factory, Synapse, Fabric, Azure SQL, ADLS), Snowflake, Teradata. • ETL Tools: Azure Data Factory, Talend Open Studio, Pentaho, Informatica, dbt, Apache NiFi. • BI & Analytics: Power BI, MicroStrategy, Apache Superset, Qlik, Looker Studio, Power Query. • Databases: PostgreSQL, MySQL, SQL Server, Oracle, Teradata, MongoDB, Cassandra. • Languages: SQL (T-SQL, PL/SQL), Python (Pandas, NumPy), PySpark. • Modeling: Data Modeling (ERD, Star Schema, Snowflake Schema). WHY CLIENTS HIRE ME: • 30+ successful data projects completed across engineering and analytics domains. • Strict focus on performance, long-term scalability, and clean, debt-free data architecture. • Clear, transparent communication and reliable, on-time delivery. • True end-to-end data expertise, tracking your data lifecycle from raw pipeline to final insight. If you need a reliable specialist who can streamline your data pipelines and turn raw tables into clear business insights, let’s talk. Click the "Invite to Job" or "Message" button to discuss your project goals.

I am a Data Scientist and ML/BI Engineer specialized in building and industrializing data & ML pipelines on Google Cloud. With 5 years of experience across large enterprises (Amazon, Equifax, SFR), scale-ups (Glovo) and multiple freelance projects in Europe, I help companies design robust data architectures, automate analytics workflows and deploy production-grade ML systems. My expertise covers the full lifecycle: • Data engineering on GCP (BigQuery, Cloud Run, Cloud Functions, Vertex AI) • End-to-end ML engineering & MLOps (model migration, training, serving, CI/CD) • BI and analytics solutions (Looker, Power BI, dbt, automated reporting) • API/Data integrations and process automation at scale Today I work through my EURL Damiani Data Consulting, supporting SMEs, scale-ups and grands comptes in modernizing their data stack and delivering actionable, production-ready solutions. 🔊​Call to Action: Feel free to contact me for data-driven solutions to your business challenges. Let's work together to turn your data into actionable insights.

I help small and mid-sized businesses turn messy, disconnected data into clear, actionable insights. Whether your data lives in spreadsheets, CRMs, or multiple operational systems, I design and build analytics solutions that let you make faster, smarter decisions — without the need to hire a full-time data team. What I do: -Build dashboards and reports in Power BI that your team will actually use. -Design analytical data models with dbt to ensure consistency and scalability. -Set up reporting pipelines and data warehouses for clean, reliable data. -Perform data analysis, including KPI tracking, exploratory analysis, and regression modeling to support business decisions. -Lead end-to-end analytics projects, overseeing planning, quality, and documentation. Why work with me: Hands-on experience across multiple business areas: HR, sales, operations, marketing, and customer service. Proven track record with both in-house and consulting roles: Inter Miami CF, Safe Credit Solutions, and now Prisma Data Works & Analytics. Practical, cost-effective solutions — no overengineering, no buzzwords. Clear communication and a focus on helping your team actually use the insights we deliver. Technical stack & tools: Power BI | SQL | dbt | Airflow | Excel | Data Warehouses | ETL pipelines Experience highlights: -Led the data migration and CRM transition to Salesforce at Safe Credit Solutions, ensuring reporting continuity. -Built dashboards consolidating multiple data sources and performed operational analysis at Inter Miami CF. -Founded Prisma Data Works & Analytics, leading a small, skilled team to deliver end-to-end analytics solutions for small and mid-sized businesses. If you’re spending hours reconciling spreadsheets, struggling to trust your numbers, or need clearer visibility into your business, I can help you build systems and dashboards that save time, reduce errors, and give you confidence in your decisions. Let’s talk about how we can make your data work for you.

I fix data that teams stopped trusting. If your scraper broke, your reports do not match, or your pipeline fails every time the source changes, that is the work I do. I make the data come in clean, get checked, and stay reliable. I have worked with data for 19 years, mostly in banks, finance, and telecom, where a wrong number has real consequences. One example: a vendor changed a CSV layout with no warning and broke a bank's reports silently, no error, just wrong numbers. I rebuilt that pipeline so it could never fail silently again. On Upwork so far: - Web scraping and data aggregation, 400+ hours, sports results from many sources - Cleaning messy data into AI-ready datasets - Data architecture for business-critical reporting - 4 projects, all with 5-star public reviews What I can do for you: - Build or fix web scrapers (Python, Selenium, Playwright, APIs) - Build or repair ETL and data pipelines - Clean and validate datasets for AI, BI, or analytics - Model and tune SQL - Prepare clean reporting data for Power BI and dashboards I use AI to work faster, but I test and own every line I deliver. Tell me your data source or the workflow that broke, and I will tell you the fastest way to fix it.

I work as a forward-deployed AI engineer — embedded directly with your team to design, build, and ship production AI systems, not just advise on them. Most AI engineers can wire up an API; few understand data at depth. I do — and that combination is the whole point. My background spans 20+ years at PricewaterhouseCoopers (PwC) and Publicis Sapient — seventeen years building software, data, and machine-learning systems, and the last three focused entirely on generative AI. That lets me bridge business strategy and technical execution for Fortune 500s and growth-stage companies. Clients span ADT, Aflac, AT&T, Capital One, Carnival, Lumen (formerly CenturyLink), Eli Lilly, Fanatics, HBO, IBM, Lennar, NBCUniversal, USAA, Visa, Wells Fargo, and Worldpay. Degrees in Computer Science and Applied Statistics, plus an MBA. 𝗪𝗵𝗮𝘁 𝗜 𝗯𝘂𝗶𝗹𝗱 Agentic AI systems — autonomous agents that reason, make multi-step decisions, and take real-world action through tools and APIs. I own the full design: LLM selection, RAG architecture, MCP server development, multi-agent orchestration, and production deployment on AWS, Azure, or GCP. The data-science layer comes built in — pipelines, predictive models, and evaluation — so agent decisions are trustworthy and measurable, not black boxes. 𝗪𝗵𝘆 𝗺𝘆 𝗯𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱 𝗶𝘀 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁 Most AI engineers don't understand data at depth. My foundation spans the full data-science stack — statistical inference, supervised and unsupervised machine learning, time-series, propensity scoring, customer segmentation, and marketing-mix and incrementality modeling — across financial services and fintech, insurance, telecom, healthcare and life sciences, media and entertainment, retail and e-commerce, consumer goods, and hospitality and travel. That depth changes how I build AI: models that are properly validated, pipelines designed for data quality, and outputs judged against real business metrics — not benchmark scores. 𝗦𝗲𝗹𝗲𝗰𝘁𝗲𝗱 𝘄𝗼𝗿𝗸 — 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗔𝗜 • ContactOS — a multi-tenant AI customer-service platform in production across voice (Twilio, Deepgram, ElevenLabs), WhatsApp, web chat, and outbound campaigns. LangGraph ReAct agents call live customer APIs in real time; per-tenant configuration via a runtime registry (a new client is a new directory, not a code change); human escalation over a WebSocket dashboard. • Replaced a specialty retailer's HubSpot CRM with a production FastAPI + React platform in weeks — built with agentic AI development tooling throughout, with AI email summarization and a shared-database architecture with the client's analytics portal, live at a fraction of the prior license cost. • Two-phase agentic engineering triage — a fast LLM classifier routes inbound tickets in under 10 seconds, then an investigation agent autonomously traces the codebase and posts structured root-cause findings to Jira. • End-to-end RAG content engine — ingests YouTube transcripts, PDFs, Kindle highlights, and web articles, then generates channel-specific content grounded in the author's own voice (not generic AI output), auto-publishing to WordPress with a companion audio file. 𝗧𝗵𝗲 𝗱𝗮𝘁𝗮 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝘂𝗻𝗱𝗲𝗿𝗻𝗲𝗮𝘁𝗵 The same modeling rigor I bring to making agent decisions measurable: • Telecom propensity — scored 6.1M customers across 200+ behavioral indicators into calibrated propensity tiers, prioritizing the highest-likelihood segments to steer self-service adoption and call deflection. • Supplemental insurer media-mix — modeled a $171M media portfolio with adstock and saturation, producing per-channel ROI with credibility intervals to guide budget reallocation. • CPG segmentation — an RFM + cohort-LTV engine on Databricks classifying 83K customers weekly, driving segment-level targeting across discounting, channel, and reactivation. 𝗖𝗼𝗿𝗲 𝘀𝘁𝗮𝗰𝗸 Python · SQL · R · PySpark | LangGraph · LangChain · CrewAI · n8n · MCP Servers | Anthropic Claude · OpenAI · Ollama | Pinecone · Qdrant · ChromaDB · pgvector · mem0 | Twilio · Deepgram · ElevenLabs · Whisper | FastAPI · React · TypeScript · Docker · GitHub Actions | PostgreSQL · MongoDB · Snowflake · Redshift | dbt · Databricks | XGBoost · scikit-learn · MLflow | Tableau · Power BI · ECharts | AWS · Azure · GCP 𝗛𝗼𝘄 𝗜 𝘄𝗼𝗿𝗸 I take ownership of delivery — I scope, architect, build, and deploy, and communicate clearly with technical and business stakeholders throughout. Whether you need a solo IC or a lead to drive a small team, the approach is the same: embedded, accountable, and shipping.