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Hello and welcome to my profile! 👋 I'm Damian, a results-oriented Data Engineer and Analyst passionate about utilizing data to drive business success. With 5+ years of experience, I specialize in turning raw data into actionable insights, optimizing complex queries, and creating impactful data visualizations. Key Expertise: 🧹 Data Cleaning & Transformation, dbt Cloud/open-source, Dataform ✨ SQL, MPP databases like BigQuery, Snowflake, RedShift, Athena 🔄 ETL Processes, Airflow (Composer, MWAA), Prefect, Dagster, custom Python/Spark scripts 🛠️ Docker, Terraform, CICD - automation 📊 Looker Studio, Looker, PowerBI: Dashboards & Reports 🌐 Fivetran, Airbyte, Snowplow, Segment 💼 Team Mentoring - code reviews, pair programming, coaching Join forces with me to unleash the potential of your data! 🚀 Don't hesitate to contact me, and let's explore how I can contribute to your upcoming project.

Your ads are only as good as the data feeding them. I fix the data. I'm a GA4/GTM tracking engineer with a developer background: 115 Upwork projects, 6,000+ hours, Top Rated Plus. I build and repair the tracking layer that decides whether your ad budget scales or burns: GA4, Google Tag Manager, server-side GTM, Consent Mode v2, Meta CAPI, and Google Ads conversions. Results clients paid for and kept: - Recovered 15-40% of conversions lost to Consent Mode misconfiguration - Cut GA4 event duplication by up to 60% with clean dataLayer architecture - Raised attribution accuracy with server-side conversion APIs for Google, Meta, LinkedIn, and Reddit - Turned hours of manual reporting into minutes with Looker Studio dashboards teams actually open What I handle end to end: - GA4 + GTM: events, ecommerce funnels, custom dimensions, cross-domain tracking - Google Ads conversion tracking and enhanced conversions - Meta Pixel + Conversion API with deduplication and event-quality checks - Consent Mode v2 and GDPR/CMP setups: Cookiebot, OneTrust, custom banners - Server-side GTM for cleaner data and stronger attribution - Shopify, WooCommerce, WordPress, Webflow, Framer, and custom JavaScript tracking - Looker Studio dashboards your team can actually use Why me and not another GTM freelancer: most can click together basic tags. I read source code, inspect the dataLayer, and debug JavaScript - so the tracking I build survives redesigns, plugin updates, and CMS migrations instead of breaking a month later. Top Rated Plus | $100K+ earned | 6,000+ hours | 115 jobs completed How we start: send me your site, ad platforms, and tracking goal. I will map your funnel and tell you exactly what is broken, what is missing, and what it takes to fix it - before you commit to anything.

Ask your ad platforms, GA4 and your back office how many orders you had last month, and you'll get three different answers. Making those three numbers agree is most of my work. The harder part is keeping them that way after the next iOS release, cookie banner or theme redesign. I'm a digital analyst at a performance marketing agency in Poland, full time, and I take on a handful of projects here alongside it. Same work, smaller teams: tracking that holds up outside a demo store, and reporting somebody actually opens on a Monday. Most of it starts inside the store. On Shopify I rebuild tracking at the source, with a custom pixel in Customer Events instead of another app that half works, checkout and order status covered, every event gated on consent. WooCommerce and custom builds get the same treatment, with the dataLayer written by hand wherever the plugin won't cooperate. And when the browser stops being a reliable place to measure from, I move the whole thing server-side with Stape: your own tracking domain, first-party cookies, Meta Conversions API with event_id deduplication so one purchase never gets counted twice, Google Ads Enhanced Conversions, plus TikTok, LinkedIn or Microsoft if that's where the budget goes. Consent is where most setups quietly break, so I test both halves of it. Nothing fires before the visitor agrees, ad_user_data and ad_personalization are set the way Google expects, and I check the denied path as carefully as the granted one, because that's the one nobody looks at. Cookiebot, OneTrust, Consentmo, or a banner somebody wrote in-house years ago. The point is numbers you can defend when legal asks about GDPR. Then there's the part you look at every week. Looker Studio for most teams, GA4 exported into BigQuery when the questions outgrow the interface, and if a client needs something Looker can't do, I build the dashboard in Next.js straight off the warehouse, so a whole marketing month fits on one screen. Getting the data there is usually n8n: pipelines pulling marketing and sales APIs into one PostgreSQL warehouse that stays current, with retries, deduplication and backfills you can re-run without breaking anything. Some of what I've built lately: - Rebuilt Shopify tracking with a custom Web Pixels pixel and theme dataLayer events, view_item through purchase, Consent Mode v2 gating, verified end to end. - Google Ads Enhanced Conversions on advanced consent: user data captured and validated on the page, but it only leaves once ad_storage and ad_user_data come back granted. - The full WooCommerce purchase funnel in GTM, custom dataLayer variables and a bit of JavaScript to get transaction and product data out of the theme. - Meta, LinkedIn and Microsoft Ads running side by side in one container, consent-aware triggers, revenue that matches across all three. - A marketing warehouse fed from five APIs with n8n, with a Next.js dashboard on top. I don't hand anything over unverified. Tracking comes with GTM Preview, GA4 DebugView, Events Manager and the actual request payloads, automations come with test runs and logs. You get a short write-up of what changed and why, you keep every account and container, and nothing in the setup depends on me still being around. Every project I've finished here is rated 5.0, with recommendations the clients wrote themselves. If you want a starting point, send me your site, your ad platforms and the one number you don't trust. I'll map how your data flows today and tell you what's broken, what's missing and what it would take to fix, before you commit to anything. I'm on CET and normally reply the same day. If you got here searching for something specific: GA4 audits and migrations, Google Tag Manager, server-side GTM on Stape, Meta CAPI and event deduplication, Google Ads conversion tracking, Consent Mode v2, Shopify Web Pixels and Customer Events, WooCommerce, cross-domain and lead tracking, BigQuery, Looker Studio, n8n, PostgreSQL, Next.js.

🎯 𝐍𝐮𝐦𝐛𝐞𝐫𝐬 𝐝𝐨𝐧'𝐭 𝐦𝐚𝐭𝐜𝐡 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐆𝐀𝟒, 𝐆𝐨𝐨𝐠𝐥𝐞 𝐀𝐝𝐬, 𝐌𝐞𝐭𝐚, 𝐚𝐧𝐝 𝐲𝐨𝐮𝐫 𝐂𝐑𝐌? ⚡️𝑇ℎ𝑎𝑡'𝑠 𝑒𝑥𝑎𝑐𝑡𝑙𝑦 𝑤ℎ𝑎𝑡 𝐼 𝑓𝑖𝑥 — 𝑑𝑎𝑖𝑙𝑦. 𝐹𝑢𝑙𝑙 𝑐ℎ𝑎𝑖𝑛: 𝑡𝑟𝑎𝑐𝑘𝑖𝑛𝑔 (𝐺𝐴4, 𝐺𝑇𝑀, 𝑠𝑒𝑟𝑣𝑒𝑟-𝑠𝑖𝑑𝑒), 𝑝𝑖𝑝𝑒𝑙𝑖𝑛𝑒𝑠 (𝐵𝑖𝑔𝑄𝑢𝑒𝑟𝑦), 𝑟𝑒𝑝𝑜𝑟𝑡𝑖𝑛𝑔 (𝐷𝑎𝑡𝑎 𝑆𝑡𝑢𝑑𝑖𝑜). ✅ 𝟔+ 𝒚𝒆𝒂𝒓𝒔 | 𝟏𝟎𝟎% 𝑱𝒐𝒃 𝑺𝒖𝒄𝒄𝒆𝒔𝒔 📍𝐖𝐇𝐀𝐓 𝐈 𝐃𝐎 1️⃣ 𝘾𝙤𝙣𝙫𝙚𝙧𝙨𝙞𝙤𝙣 𝙩𝙧𝙖𝙘𝙠𝙞𝙣𝙜 & 𝙖𝙣𝙖𝙡𝙮𝙩𝙞𝙘𝙨 𝙨𝙚𝙩𝙪𝙥 GA4 (web + app), Google Tag Manager (web + server-side), enhanced ecommerce, cross-domain tracking, Consent Mode v2. Conversion tracking for Google Ads, Meta (Pixel + Conversions API with deduplication), LinkedIn, Microsoft Ads, Bing UET. Server-side tagging with Stape or Google Cloud. Tracking on any platform — Shopify, Webflow, Framer, WordPress, ClickFunnels, custom sites. 2️⃣ 𝘿𝙖𝙨𝙝𝙗𝙤𝙖𝙧𝙙𝙨 & 𝙧𝙚𝙥𝙤𝙧𝙩𝙞𝙣𝙜 (𝘿𝙖𝙩𝙖 𝙎𝙩𝙪𝙙𝙞𝙤 & 𝙂𝙤𝙤𝙜𝙡𝙚 𝙎𝙝𝙚𝙚𝙩𝙨) Data Studio (formerly Google Looker Studio) dashboards on BigQuery, Google Sheets, or direct connectors — including custom HTML/CSS visualizations and community components when standard charts aren't enough. Agency multi-client reporting, GoHighLevel reporting, Supermetrics & Windsor setups. Clean data model underneath, so dashboards stay fast and don't break when a source changes. 3️⃣ 𝘿𝙖𝙩𝙖 𝙥𝙞𝙥𝙚𝙡𝙞𝙣𝙚𝙨, 𝘽𝙞𝙜𝙌𝙪𝙚𝙧𝙮 & 𝙀𝙏𝙇 Automated pipelines from ad platforms, CRMs, ERPs, and APIs into BigQuery or Snowflake — Cloud Run / Cloud Functions (Python, Node.js) or Apps Script, with layered data models (raw → staging → marts / medallion architecture), scheduled transformations, and upsert patterns so reports never show empty tables mid-refresh. Real examples: SAP Business One + ADP + Copper CRM → BigQuery warehouse with full SQL modeling layer; Facebook Ads API → BigQuery multi-account pipeline; SEMrush API → Sheets → Looker Studio SEO reporting; GA4 Data API → Sheets automation. 4️⃣ 𝘼𝙩𝙩𝙧𝙞𝙗𝙪𝙩𝙞𝙤𝙣 & 𝘾𝙍𝙈 𝙞𝙣𝙩𝙚𝙜𝙧𝙖𝙩𝙞𝙤𝙣 Connecting forms, booking tools (Cal scheduling platform, Calendly, HubSpot bookings), and CRMs (HubSpot, Marketo, Pardot, GoHighLevel, Copper) with ad platforms and analytics so leads keep their real source. Offline conversion imports, enhanced conversions, UTM architecture, lead-source debugging, deduplication between platforms. 5️⃣ 𝘼𝙪𝙙𝙞𝙩𝙨 & 𝙘𝙤𝙣𝙨𝙪𝙡𝙩𝙞𝙣𝙜 Conversion tracking audits and fixes (Google Ads, Meta, GA4 & Shopify), GTM container audits, consent/GDPR compliance reviews, duplicate conversion cleanup, and root-cause analysis when numbers disagree between GA4, ad platforms, and your CRM. I read network requests, HAR files, and container exports — not just the reporting UI. I also consult teams and deliver full documentation — technical and non-technical — so any specialist can work with the final setup. 🔑 𝐇𝐎𝐖 𝐈 𝐖𝐎𝐑𝐊 ✔️Minimal changes to working infrastructure — I fix what's broken without rebuilding what isn't ✔️Errors surface loudly, never silently — pipelines and tags that fail should tell you ✔️Everything documented in plain language, so your team isn't dependent on me forever ✔️Honest scoping — if something isn't worth building, I'll say so before you pay for it ⚒ 𝐒𝐓𝐀𝐂𝐊 Google Analytics 4 · Google Tag Manager (web + server) · Stape · BigQuery · Snowflake · Looker Studio · Google Cloud (Cloud Run, Dataform, Cloud Functions, Scheduler) · Python · JavaScript · SQL · Apps Script · Meta Conversions API · Google Ads · Bing UET · HubSpot · Marketo · Pardot · GoHighLevel · Windsor · Supermetrics · Matomo · Plausible · SEMrush API 🤝 𝑻𝒚𝒑𝒊𝒄𝒂𝒍 𝒄𝒍𝒊𝒆𝒏𝒕𝒔: SaaS companies, B2B services, e-commerce, manufacturing, and marketing agencies that need tracking, attribution, and reporting to work as one system. 👉 Message me with what's broken (or what's missing), and I'll tell you honestly what it takes to fix it.

I am a Senior Data Engineer with 9+ years of experience architecting high‑performance data pipelines, cloud data warehouses, and enterprise BI solutions. I specialise in DBT‑driven transformation layers, BigQuery optimisation, and large‑scale ETL/ELT orchestration – turning raw, fragmented data into trusted, analytics‑ready assets that power strategic decisions. My approach combines deep data modelling expertise with modern engineering practices: version‑controlled transformations, automated testing, CI/CD for data, and cost‑aware cloud design. I deliver systems that are not only scalable and reliable but also maintainable and well‑documented for your entire team. ✔️𝐒𝐩𝐞𝐜𝐢𝐚𝐥𝐢𝐳𝐞𝐝 𝐄𝐱𝐩𝐞𝐫𝐭𝐢𝐬𝐞. - DBT (Data Build Tool): Advanced modelling, incremental strategies, macro development, and rigorous data testing for analytical warehouses. - BigQuery Optimisation: Partitioning, clustering, slot management, and query cost control – delivering sub‑second responses on petabyte‑scale data. - Big Data Processing: Spark (PySpark) and Kafka for stream/batch processing, with efficient handling of high‑volume, high‑velocity datasets. ✔️𝐒𝐭𝐫𝐨𝐧𝐠 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞 𝐢𝐧 - E‑commerce & retail analytics: building 360° customer views, inventory forecasting, and real‑time sales dashboards. - Financial data platforms: regulatory reporting, fraud detection pipelines, and GDPR‑compliant data masking. - Real‑time streaming architectures: Kafka + BigQuery + dbt for near‑real‑time operational intelligence. ✔️𝐏𝐫𝐢𝐦𝐚𝐫𝐲 𝐒𝐭𝐚𝐜𝐤. - Cloud Platforms: GCP (BigQuery, Composer, Pub/Sub), Azure (Data Factory, Synapse, Databricks), AWS (Glue, Redshift, S3). - Warehousing & Lakes: BigQuery, Snowflake, Azure Synapse, MSSQL, PostgreSQL, MySQL. - Transformation & Orchestration: dbt (core/cloud), Apache Airflow, Prefect, Azure Data Factory. - Languages: Advanced SQL, Python (Pandas, PySpark, Polars), DAX, M (Power Query). - BI & Visualisation: Power BI (Service, Premium, Paginated Reports), Tableau, Looker Studio. - Big Data Tech: Apache Spark, Kafka, Flink, Databricks (Delta Lake). - DevOps for Data: Git, CI/CD (GitHub Actions, Azure DevOps), Docker, Terraform (basic). - Data Governance: RLS, column‑level security, data lineage, and quality monitoring (Great Expectations). ✔️𝐖𝐡𝐞𝐭𝐡𝐞𝐫 𝐲𝐨𝐮 𝐧𝐞𝐞𝐝 𝐭𝐨 - Migrate legacy ETL to a modern dbt + BigQuery stack with full CI/CD, - Build a high‑throughput streaming pipeline that ingests millions of events per second, - Design a self‑service semantic layer that empowers business users with reliable KPIs, - Or optimise your existing warehouse for cost and performance without sacrificing freshness, I deliver a clear roadmap, measurable improvements, and a system your team can confidently own. ✔️𝐖𝐡𝐚𝐭 𝐲𝐨𝐮 𝐠𝐞𝐭 ✅ A data platform built for scale – not just today, but for 10x growth ✅ Cloud cost optimisation that reduces your monthly bill by 20‑40% ✅ Daily updates (Slack/email) with progress, blockers, and next steps ✅ Clean, modular dbt code with full documentation and automated tests ✅ Production‑ready pipelines with monitoring, alerting, and rollback strategies Message me or invite me to a quick 15‑min call – I will walk you through a tailored architecture sketch for your project. Keywords: Data Engineer, DBT, BigQuery, Big Data, ETL, ELT, Cloud Analytics, Power BI, MSSQL, Python, SQL, GCP, Azure, AWS, Data Warehousing, Snowflake, Databricks, Apache Airflow, Kafka, Spark, PySpark, Data Pipeline, Business Intelligence, Dashboard, Data Modelling, DAX, M, Data Lake, Data Integration, E‑commerce Analytics, Financial Data, Real‑time Streaming, CI/CD, DevOps, Data Governance, Performance Optimisation, Cloud Migration, Senior Data Engineer, Remote, Full‑time.

The only way to make a success of your AI project: Stable Infrastructure & data flows - Programmed Automations - AI API Integration - AI Agents and RAGs Google Apps Script is the best tool to automate your business processes. Zero operation costs. Google-guaranteed security and stability. We practice AI-assisted development (Google Antigravity, VSCode, Gemini Pro, Claude Code, Codex, Cursor, Copilot, etc.) with full human review of every outcome. We build our own AI agents and RAGs; we work with MCPs — and we can build all of that for you too. Zapier, n8n, and Make are fine for basic tasks — but as soon as you need deep integration, they fall short. And they cost money. Get in touch through direct message, invite me to your project, or book a consultation! ⌛ We will help you save your time! Sound familiar ❓ ⭐ You have a workflow that uses Sheets, Docs, Gmail, Calendar, Drive — and at some point you thought: "this should just happen automatically." ⭐ So you Googled it. Every answer pointed to Zapier, Make, or n8n. You signed up, watched a few videos, built something that almost worked — and hit a wall the moment your use case got slightly specific. ⭐ You asked ChatGPT to help. It gave you a confident answer. You followed it step by step. It didn't work. You asked again. It gave you a different confident, detailed answer. That didn't work either. Two hours became an evening. ⭐ You tried a few more things, spent some money on a paid plan to unlock a feature you needed, and eventually got something running — something fragile, something you don't fully understand. ⭐ At some point you got a hint: Google Sheets and Drive live in the same ecosystem and talk to each other natively. ⭐ You looked into Google Apps Script. It seemed powerful. It also seemed like code. You asked AI to write it for you. It wrote something. It didn't run. You debugged for a while, then closed the tab. ⭐ Now you have a half-working Zap, a script that does 60% of what you need, a growing subscription bill, and a nagging feeling that someone who actually knows what they're doing would do a better job. ⭐ That's where I come in. What I can do for you ❓ ⭐ Help you formulate project requirements, even if you aren't sure about them yet ⭐ Talk through all the details of your idea and put together an initial implementation plan ⭐ Identify potential shortcomings, technology limitations, and help you set priorities ⭐ Clearly point out what needs to happen before we start and after we finish All projects are "technically possible" — but not all are "cost-effective" or "reasonable." How we will do this ❓ 🔥 Initial stage: detailed analysis and planning (kick-off meeting, workflow mapping, project plan) 🔥 Preparation: share necessary resources and account access, sign the contract and NDA if needed 🔥 Data foundation: we structure and clean your data first. We organize it properly and set up retention pipelines so everything downstream is reliable. 🔥 Deterministic automation: once the data is solid, we build rule-based automations that handle the predictable, repeatable work. These don't need AI — they just need to be correct, fast, and dependable. 🔥 AI integration: only at this stage do we bring in LLMs — where they actually add value. Natural language interfaces, intelligent triage, summarisation, anomaly detection, generative outputs. 🔥 Ongoing review: you review developments and provide feedback throughout 🔥 Testing: once development and corrections are complete, you test everything end to end 🔥 Delivery: final corrections, bugs squashed, project concluded 🔥 Aftercare: bugs found later are fixed for free; new ideas become new milestones. How can you be sure ❓ Scroll down and read the feedback from our clients. All words are genuine, all people and companies are real and verified by the platform. Can we show examples of our work ❓ General descriptions — yes. Code or data — no. Most of our work is proprietary and covered by NDAs. Let's get in touch through direct message, invite me to your project, or book a consultation! API integrations we have worked with: Google Workspace, AI Studio, Claude Code, SDLC, JSON, XML, Markdown, Google Sheets, Calendly, GoHighLevel, Codex, AI agents, RAG, MCP, Multi-agent systems, Google Docs, Stripe, Asana, Jira, Slack, Cloud Storage, QuickBooks, HubSpot, Monday, OpenAI API, Gemini API, Firebase, Firestore, GitHub, Harvest, ClickUp, Cerbo, Intercom, Trello, WordPress, Facebook Atlas, Upwork, GMB, Gmail, Tableu, Airtable, Google Calendar, Google Places, Google Place Details, Google Maps, Google Business Profile, GA4, Google Analytics, Google Ads, Typeform, Instapage, CryptoCompare, Bittrex, Invenias, EOD Historical Data + others.