Hire the Best Northern Data Systems EDIFICE Specialists

I'm a data professional with a Bachelor degree in computer science, with 8+ years of experience in the field and have been working in small and big data enterprise solutions. During my professional path, I worked in several roles like DBA, Data Architect, Data Engineer, Data Governance and Business Analytics team support. My experience comes from hybrid environment projects with cloud providers like AWS, Google and Azure. I can mention some of the most challenging projects in my professional career where I am proud to produce an impact in the organizations. The actual Chilean Public Education payment service, which managed almost 3,2% of the country's PIB can calculate and assign the Education money for every public school in the country using variable metrics managed by user, my expertise in Databases and integrations was key in the actual calculation workflow process. I was able to developed a service to recollect Chilean Public transportation data from real-time social network and combine with the buses GPS data for analytics, so the Managers could make decisions for quality service improve from the service user perspective taking actions rapidly. I was part of the team that create and deploy the first Africa online tax service in Kenya, where I took in charge of the modeling and support of the Oracle operational database, the service was a game changing, lowing in big manner, the cost of the tax recollection in Kenya. And lastly I design and had feed the Datawarehouse of a Chilean financial big company with the data required that allowed to the company made the correct decision about what king of products needed to focus. All of it, with a mix of database services like Azure SQL Server, GCP Bigquery, MongoDB and PostgreSQL. With the work on mixed environments and budgets, I can mix open-source technologies like low-code solutions like Pentaho, Airflow, db and Processmaker, with proprietary services in the cloud like lambda functions, Athena, Google Compose, Azure ADF or Glue, plus coding skills like SQL, python, Java and Regular Expressions (for text data query). I also have experience with Data visualization tools like Google Data Studio, Clickview, PowerBI, SSRS, Webfocus and Pentaho Reporting Services, knowledge of it because of the need to support BI Teams in some projects. Its seems likely that I missed a more specialized technical profile, but it was the result of the need to work with disparate clients and industries, however I feel very confident with the whole enterprise data journey path, from data modeling and processing to data visualization and it allows me to see the big picture in data solutions implementations. Regards.

I fix data products that were built fast, sometimes vibe coded, and now break in production. Shipping fast was the right call and my job is making the product hold up. If your customers are finding problems before your team does (silent failures, numbers that don't match the source, timezone bugs in your history), that's what I get hired to fix. Recent results: - Inherited a supply chain analytics product that didn't work in production and rebuilt it into the platform the client now runs their business on, then helped hire and onboard the engineers who maintain it. More than happy to talk about what was broken and what changed. (Python, FastAPI, PostgreSQL, dbt) - Primary architect on an invoice and inventory platform (10 months, ongoing): wrote the first 16 architecture decision records the team builds against, built the extraction pipeline that turns supplier invoices into structured data at 90%+ accuracy across 30,000+ invoices, and wrote the tests that catch money-handling bugs (decimal precision, dropped reference numbers) before a user ever sees them. (Python, PostgreSQL, dbt, FastAPI, LLM extraction) - Kept 400K+ records a day flowing from 10+ sources into the one warehouse an entire e-commerce company reported from. (Python, BigQuery) How I work: bad upstream data gets caught at the door, not on your dashboard (pandera, Pydantic). Your numbers reconcile against the source, so "why doesn't this match" stops being a recurring meeting (dbt, tested transformations). Failures reach you as an alert, not as a customer complaint. And I won't only deliver the technical work: I go the extra mile (or kilometer) to foster a respectful, teamwork-driven environment, and I leave behind documentation your team can actually use. Stack: Python, PostgreSQL, dbt, FastAPI, SQLAlchemy, BigQuery, Docker, AWS, GCP, DigitalOcean Focus areas: energy and market data (ISO feeds: CAISO, ERCOT, PJM), supply chain and logistics, e-commerce, and vertical SaaS data backends. A good fit: funded startup or established SMB with real data volume and no dedicated platform team yet. Not a fit: website builds (even broken ones), greenfield ML research, or automation workflows. Sounds like your situation? Book a consultation below. When you do, I'll ask for two or three sentences on what breaks and how often, so we spend the call on diagnosis instead of introductions. You'll leave with a written summary and a prioritized fix list, whether or not we work together afterward.

Hi, I'm Movses, a Data Engineer with 10+ years of experience. I'm a certified AWS Data Engineer with extensive experience in the AWS data stack. You name it, I've done it. More than data engineering, I love database development. With Oracle, Postgres, SQL Server, Snowflake, I feel home. SQL is my native language, and I code in Python, Scala, PL/SQL, and Bash. I specialize in creating ETL/ELT jobs, data pipelines, and orchestration jobs. I'm here to help you overcome challenges and set optimal data goals and designs. I stay involved after the project wraps up, not for the money, but because I only take on projects that genuinely interest me. I believe in delivering results that matter to both of us.

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!

⏰ Available 24/7 – Long-term & High-impact Projects Hi, I’m Nghi, a Senior Data Engineer and Data Architect with a strong backend foundation, now focused on building high-performance analytics platforms, explainable data pipelines, and production-grade cloud architectures. I help companies transform unreliable, slow, or opaque data systems into scalable, well-documented, and business-trustworthy platforms. 🧠 WHAT I SPECIALIZE IN 🏗️ Data Architecture & Platform Design - Designing modern lakehouse & warehouse architectures - dbt-first analytics engineering with testing, freshness & lineage - Event-driven and batch hybrid pipelines - Data quality frameworks & SLA monitoring - Customer-facing data explainability systems Tools: dbt, Dagster, Airflow, Spark, Kafka, Snowflake, BigQuery, Redshift, PostgreSQL, DuckDB, ClickHouse ⚡ Database Performance Engineering - If your queries are slow, costs are high, or dashboards lag, This is my zone - Query plan analysis & index strategies - Warehouse cost optimization (Snowflake, BigQuery, Redshift) - OLTP & OLAP performance tuning - High-concurrency workload design 🔄 Reverse ETL & Operational Analytics - Syncing analytics back to CRMs & internal tools - Building real-time metrics pipelines - Feature-store style transformations 🕷️ Enterprise-grade Web Data Extraction - I don’t just scrape pages, I build durable data acquisition systems: - Complex ASP.NET, JS-heavy, authenticated & paginated systems - Anti-bot bypassing & failure-recovery pipelines - Headless browser automation + async scraping - Real-estate, finance, campaign-finance & marketplace platforms ☁️ Cloud Infrastructure - AWS | Azure | GCP - EMR / Dataproc / Glue / Dataflow / Synapse / BigQuery / Redshift - Terraform-based deployments - Cost-aware architectures - Kubernetes + Dockerized data services 🧪 What You Get Working With Me ✔️ Production-ready pipelines ✔️ Clean, testable dbt models ✔️ Well-documented architecture diagrams ✔️ Transparent data logic for non-technical stakeholders ✔️ Systems that scale beyond MVP ✔️ Honest advice and not over-engineering 🏆 Ideal Projects 👍 Data warehouse migrations 👍 Broken pipelines that need debugging & stabilization 👍 Analytics platforms that lack trust or explainability 👍 Performance bottlenecks costing thousands per month 👍 Long-term data platform ownership ❣️ Why Clients Stay Long-Term 🍀Clear communication 🍀 Business-first thinking 🍀 No black-box systems 🍀 I build systems others can maintain 🇻🇳🇻🇳🇻🇳🇻🇳 If your data platform feels fragile, slow, or impossible to explain to customers, I can fix that. Let’s make your data system something you can confidently stand behind.

You're probably generating more data than you know what to do with. Most of it sits in dashboards nobody opens, or feeds reports nobody trusts. I fix that. 25 years building data infrastructure for companies from startups to Fortune 500, across the US, Latin America, and Europe. On Upwork since 2016, Expert-Vetted (their top 1% of independent talent). I'm not an agency, and I don't do offshore handoffs. It's just me, doing the work you need done. And my work history can testify that I can get it done. I've been the fractional CTO reporting to CEOs at data-heavy companies, the data lead serving a C-suite, and the extra pair of senior hands inside an existing team. The structure can be flexible, but I'll never loose the standards. What I actually deliver: Reporting people trust. Not dashboards that look impressive in meetings, but numbers that trace back to source and survive hard questions. A recent client discovered they'd been overstating ARR for years. I rebuilt it from transaction data and now the figure holds up in due diligence. AI and ML that reaches production. I've shipped forecasting models, document extraction, and analytics agents that run daily in live businesses. One recent model beat the client's specialist analyst on 7 of 10 product categories. Where it lost, I told them why, because knowing the limits is part of the job. Audits that find real money. Pricing analysis for a SaaS client surfaced $193K a year in unintended cross-subsidies between customer tiers. A BI audit for a UK wholesaler found board reports that couldn't be traced to source, plus the path to fix them. Integrations that stop being fragile. QuickBooks, Unleashed, Salesforce, SAP, Chargebee, Snowflake, and the long tail of tools mid-market companies actually run. Stack: Python, R, SQL (PostgreSQL, MySQL, MS SQL), Snowflake, AWS, Azure. BI: Qlik Sense, Power BI, Tableau. AI/ML: Anthropic Claude, OpenAI, custom models. Plus GIS, forecasting, and marketing analytics when the problem calls for it. Tell me what's not working and I'll tell you honestly whether I'm the right person for it. Sometimes I'm not, and I'll say so. When I am, you'll know within one conversation.