Playwright Public Records ETL Automation

@AwaisChaudhry

Hello, I understand you want a production-grade ETL pipeline that uses Playwright (Python) to hourly-scrape publicly accessible records, cleanse and normalize them, and load into a Postgres database on Supabase with maintainable architecture and cloud-native deployment. My approach is to build a modular codebase with clear boundaries: scraping in a dedicated module with headless Playwright, retry logic, and rate-limiting backoff; a transformation layer that enforces type checks, standardization, and data integrity; a storage layer with a well-designed Postgres schema, upsert logic, and migrations; packaging into a Docker image, CI/CD to Cloud Run with environment configs and secret management; and observability via JSON logs, centralized error tracking, and a lightweight dashboard using Cloud Monitoring or Grafana. The repo will include a clear README, environment templates, and a one-command local dev with docker-compose up. This approach ensures maintainability, scalability, and easy future extension by contributors. What is the exact sample spec for the cleaned/normalized data so I can align field names and data types? What are the mandatory and optional fields to extract from the public-records site? Do you have an existing Supabase project or test database to bootstrap the initial Postgres schema and migrations? Should the pipeline run in a strict hourly window or is a best-effort hourly schedule acceptable? How should we handle rate limits and politeness on the target s

@ZohaibRoy

⭐⭐⭐⭐⭐ Build a Robust ETL Pipeline with Playwright and Postgres ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you're looking for an expert to build an ETL pipeline using Playwright. Look no further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for ETL solutions. I will ensure the pipeline is modular, well-documented, and scalable for future needs. ➡️ Why Me? I can easily create your ETL pipeline as I have 5 years of experience in Python automation, web scraping, and data management. My expertise includes browser automation, data transformation, and database management. Besides, I have a strong grip on Docker, CI/CD practices, and cloud deployment, ensuring a smooth and efficient project. ➡️ Let's have a quick chat to discuss your project in detail. I can showcase samples of my previous work, demonstrating my skills in building ETL pipelines. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ Python Programming ✅ Playwright Automation ✅ Data Extraction ✅ Data Cleaning ✅ Data Normalization ✅ Postgres Database ✅ Docker Packaging ✅ CI/CD Integration ✅ Cloud Deployment ✅ JSON Logging ✅ Error Tracking ✅ Monitoring Tools Waiting for your response! Best Regards, Zohaib

@Guptapuru304

We have successfully executed similar ETL automation projects and are eager to bring our expertise to your Playwright Public Records ETL Automation initiative. Our understanding of the project highlights the importance of a robust, modular, and scalable codebase that facilitates long-term maintainability. This aligns well with our strengths in AI-first product development and automation. With over 8 years of experience, we've honed our skills in Python, PostgreSQL, and data extraction, ensuring the creation of a seamless ETL pipeline. Our proficiency with Docker, CI/CD, and cloud-native architectures guarantees a scalable and resilient deployment. Plus, our background in structured logging and monitoring will provide you with the comprehensive observability you require. Our portfolio showcases numerous projects where we’ve integrated intelligent data pipelines and cloud-native solutions, ensuring that each step from scraping to deployment is meticulously handled. How would you describe the expected data structure for normalization? We’re excited to collaborate with you to create an efficient, future-proof solution. Please let us know a convenient time to discuss this further. Looking forward to a promising partnership. Q: Could you share more about the sample spec for data normalization? Q: Is there a preferred tool or service for monitoring and logging? Best regards, Puru Gupta

@LiveExperts

Hello, As a skilled Python developer with extensive experience in Data Extraction, I'm confident that I can handle the complexity and scale requirements of your Playwright Public Records ETL Automation project. I thoroughly comprehend how important a production-grade ETL pipeline is for any organization, so rest assured that I will prioritize its long-term maintainability and scalability. My special focus on clean code, modularity, and clear documentation can guarantee easy extensibility without compromising on functionality. In addition to my proficiency in headless Playwright Browser Automation and data transformation processes, I have a deep understanding and expertise in PostgreSQL and upsert logic. Moreover, I have hands-on experience in building Docker images with environment-specific configurations and secrets management. Migrations, logging and structured JSON logging for observability are no doubt my forte, which will align perfectly with your monitoring plans. What sets me apart from others is the ability to deliver an end-to-end solution that not only meets but also exceeds the acceptance criteria. My comprehensive README instructions, environment templates, and the one-command local dev setup (`docker compose up`) ensure a smooth handover of the project. Partnering with Live Experts means partnering with excellence. Let's have a conversation to understand better how we can make this journey successful together! Thanks!

@intelliresponse

As an experienced Python developer with exceptional skills in data extraction, ETL, and web automation, I am the perfect fit for your Playwright Public Records ETL Automation project. For over 13 years, I have been at the forefront of creating tailored Python web automation and scraping solutions for clients globally. Some of my notable ventures have included sports data extraction from platforms like FlashScore and VFS Global VISA Booking Bot with sophisticated stealth browser and Captcha Solver. I'm well-versed in Playwright, BeautifulSoup, Selenium, Scrapy - all tools essential for your project. Securing a clean and standardized data flow is fundamental to any ETL process, and that's where my expertise shines. I'm adept at constructing efficient PostgreSQL schemas on Supabase that incorporate reliable upsert logic, indexes, migrations; so you can rest assured about the integrity of your data even as the pipeline scales through time. Furthermore, I am incredibly comfortable deploying solutions using Docker CI/CD on Cloud Run and implementing structured JSON logs for observability - pivotal for any production-grade pipeline. Building user-friendly environments packaged with ample documentation is also an area of strength. To top it off, my wide repertoire of skills includes not only creating efficient fron

@irsolutions

With over 10 years of experience in web and mobile development, I understand the importance of building a production-grade ETL pipeline that is not only efficient but also scalable and maintainable. Your project requires a Playwright Public Records ETL Automation solution that extracts public data, cleanses it, and loads it into Postgres on Supabase. I am well-equipped to meet these needs and exceed your expectations. In the realm of automation and transformation, I have successfully executed similar projects in the past, ensuring data accuracy and reliability. My expertise in building well-designed Postgres schemas and deploying Docker images to Cloud Run aligns perfectly with your project requirements. I am confident in my ability to deliver a solution that meets all core build expectations and acceptance criteria outlined in the job description. If you are ready to take your ETL pipeline to the next level with a cloud-native, self-healing service, I am here to help. Let's discuss how we can bring your project to life and ensure its long-term success.

@leadconcept

Greetings, I understand you need a production-ready ETL pipeline that scrapes public records via headless Playwright, cleans and normalizes the data, and loads it into Postgres on Supabase, with modular code, CI/CD deployment to Cloud Run, observability, and scalable architecture. To align scope, a few quick questions, 1. Will the site require login or CAPTCHA handling, or is it fully public, 2. Do you prefer Cloud Monitoring or Grafana for the dashboard and alerts, 3. How many concurrent records per run should the initial pipeline handle, Our delivery team includes Python engineers experienced with Playwright automation, ETL design, Postgres schema optimization, Dockerized deployment, CI/CD pipelines on GitHub Actions or Cloud Build, and observability with structured logging and metrics dashboards. We handle retries, rate limiting, unit/integration testing, and one-command local setup. Let us chat so we can review field mapping, sample data, and job scheduling, the bid amount is a placeholder to submit. Regards, Yasir LEADconcept PS: We can share ETL repos, Playwright scraping examples, and monitoring dashboard demos on request.

@DeveloperStation

Hi Paul, We’ve built production-grade web scrapers that evolved into fully-fledged ETL pipelines, handling everything from data extraction to transformation and loading into databases. With our extensive experience in CI/CD, we can ensure your pipeline is robust and self-healing. We’ve also developed a custom Playwright-based solution for a client, where we implemented advanced features like proxy rotation, user-agent switching, and smart retry logic to handle dynamic web pages effectively. Let’s schedule a quick 10-minute call to discuss your project in more detail and see if I’m the right fit for your needs. Best, Adil

@JustinJcob

⭐⭐⭐⭐⭐ Expert in Building Robust ETL Pipelines: I got you! Specializing in Playwright automation (Python), Postgres on Supabase, and Docker deployment for reliable, scalable operations. By prioritizing maintainability and scalability, I ensure a modular codebase with thorough documentation for seamless future extensions. Let's have a quick chat to discuss your project in detail and review samples of my previous work. I look forward to collaborating with you! Kind regards, Haroon Z .

@maximg10

⭐Hi, I’m ready to assist you right away!⭐ I believe I’d be a great fit for your project since I have extensive experience building scalable, production-grade ETL pipelines using Python, Docker, and cloud services like Cloud Run and Supabase. I can deliver a robust, well-documented solution within your timeline and budget, designed for long-term maintenance and easy extension. I’ve developed similar pipelines that automate web scraping with Playwright, handle complex data transformations, and deploy seamlessly to cloud environments with CI/CD setups. I also have strong expertise in designing database schemas, setting up monitoring dashboards, and implementing reliable retry and error handling. This project will automate data collection from a public records site, reducing manual effort and ensuring data accuracy. It will provide a reliable, scalable pipeline that loads clean, normalized data into Postgres, with full observability and easy deployment. If you have any questions, would like to discuss the project in more detail, or would like to know how I can help, we can schedule a meeting. Thank you. Maxim

@dvcontact

Hi there, What if your public records pipeline ran flawlessly every hour without a single manual intervention—would you like me to build a working prototype of the end-to-end flow this week so you can see it in action? I'll deliver a production-grade, self-healing ETL that combines smart Playwright automation with bulletproof data validation, modular Python architecture, and full observability—designed for your team to extend confidently without breaking anything. Let's connect and align on your data spec and monitoring preferences so we can get this live and maintainable. Best, Smith

@anayapallavi

Hello, I’d be glad to assist with your project. I have experience handling similar work and will make sure everything runs smoothly from start to finish. My goal is to deliver quality results on time and ensure you’re completely satisfied with the outcome. Let’s connect to discuss your project details — I’m ready to get started right away. Best regards, Pallvi Gupta

@kaliansh

Hello, I have read the project description you have shared and I found that I am the right fit for the project. I have previously worked on similar projects to gather data using browser automation and saving data in a database. Before we proceed further kindly share the website you want to extract data from. I want to analyse the website comprehensively so I can confirm if browser automation is actually required and it's the only solution or we could utilise the backend api calls too. If you have any queries kindly feel free to ask. I have read the acceptance criteria so I'll be the one hosting the container on cloud. Anshu.K

@techplusintl

Hi there, ★★★ Python / Data Scraping Expert ★★★ 6+ Years of Experience ★★★ I will successfully implement the ETL pipeline for your project by following a structured approach: 1. Analyze the public-records website and define the scraping strategy (8 hours) 2. Develop the Playwright script for data extraction, incorporating retry logic and rate limits (10 hours) 3. Create a transformation layer for data cleaning and normalization before loading into Postgres (8 hours) 4. Design a robust Postgres schema on Supabase with upsert logic and indexing (6 hours) 5. Package the application in a Docker image and set up CI/CD for deployment to Cloud Run (10 hours) 6. Implement observability features with structured logging and monitoring (5 hours) 7. Write clear documentation and README for future contributors (4 hours) What I need from you: 1. Access to the public-records website and any specific data requirements you have. 2. Sample specifications for the cleaned data format. 3. Details about your preferred monitoring stack for observability. I look forward to connecting at your convenience to ensure the project's success. Best Regards, TechPlus Team

@mykhaylob4

✋ Hi there. I can build your Playwright ETL automation to extract public records, clean and normalize the data, and load it into Postgres on Supabase as a fully production-ready, scalable pipeline. ✔️ I have strong experience with Python Playwright automation, cloud-native ETL pipelines, and modular, maintainable code. In previous projects, I designed scraping systems that respect rate limits, handle retries gracefully, and integrate end-to-end with databases while providing full observability and logging. ✔️ For your project, I will implement headless Playwright extraction with robust error handling, a transformation layer for data normalization and validation, and a Postgres schema optimized for upserts and performance. I will also containerize the pipeline for Cloud Run deployment with CI/CD, secrets management, and monitoring dashboards for job metrics. ✔️ I will provide a complete, documented repository with one-command local setup, unit and integration tests, and guidance for future contributors so the pipeline remains maintainable and extendable. Let’s chat to discuss your ETL workflow and deployment preferences. Best regards, Mykhaylo

@pvsysgroupinc

I work across a wide range of digital technologies, including: SAP and Odoo ERP solutions Staff augmentation services Digital transformation and IT consulting Custom software development and web/mobile app development Industrial automation solutions ERP/CRM implementation and ongoing support With a highly skilled and passionate team behind me, I help organizations live, thrive, and evolve through innovation. I don’t just deliver technology — I help create the momentum your business needs to grow, adapt, and lead.

@vorasiddh4it

Hello Paul, I can build your production-grade, cloud-native ETL pipeline exactly as specified — from Playwright scraping to Supabase/Postgres loading, Docker packaging, CI/CD, and monitoring. I’ve built multiple hourly/near-real-time automated scrapers with Playwright + Python and can show demo code immediately before we finalize the deal. Why I’m a perfect fit Browser Automation: • Playwright (Python), headless mode, smart pacing, rate-limit friendly • Built-in exponential retries, session reuse, anti-block patterns ETL Engineering: • Data normalization, schema validation, Pydantic-based cleansing • Transformation pipelines with modular, testable components Database Layer: • Supabase/Postgres with UPSERT, partitioning, indexing, migrations Cloud & Deploy: • Dockerized ETL, deployed to Cloud Run via GitHub Actions CI/CD • Secrets via Google Secret Manager Observability: • Structured JSON logs + Grafana dashboards + alerting • Error tracking (Sentry / Cloud Logging) Relevant Projects • “GovData Hourly Crawler (Playwright + Postgres)” — public-record ETL with Cloud Run • “Real-Time Compliance Monitor” — normalization + Pydantic + CI/CD • “Financial Filings Scraper Pipeline” — Dockerized ETL with dashboards & alerts What you’ll get Fully modular, contributor-safe repo One-command dev setup (docker compose up) Clean, normalized data meeting your sample spec Scalable & future-proof architecture Ready to start and can show working Playwright ETL samples on request.

@reedsystems

Hi, I’m excited to take on your project for setting up a production-grade ETL pipeline using Playwright (Python) to scrape public records from a website hourly. I’ll ensure the codebase is modular, clearly documented, and suitable for future contributors to extend seamlessly. Key features include: - Headless browser automation with smart pacing and built-in retry logic while respecting site rate limits. - A robust transformation layer that standardizes, normalizes, cleanses, and validates data before database interaction. - A well-designed Postgres schema on Supabase, complete with upsert logic, indexes, and migrations. - Dockerized deployment to Cloud Run via CI/CD (GitHub Actions or Cloud Build), including environment-specific configurations, secret management, and unit/integration tests. - Observability through structured JSON logs, centralized error tracking, and a lightweight dashboard for job success counts, latency, and row insert metrics. This pipeline will be fully automated with no manual intervention required. Data will arrive in Postgres as per the provided sample spec, and monitoring will be set up to ensure visibility into log, metric, and alert data through your chosen stack. Clear README instructions, environment templates, and a one-command local dev setup (`docker compose up`) will also be included in the repository. You can check my portfolio on my profile for references. Let's discuss further and get this pipeline running! Best, Olasunkanmi Taiwo Ridwan

@zeljkoi6

Hi, I’m excited about the opportunity to develop your Playwright ETL pipeline for public records. With extensive experience in Python and building scalable ETL processes, I will ensure the data extraction, transformation, and load phases are robust and efficient. I focus on modular code that adheres to best practices in documentation, making future contributions seamless. I am ready to kick off this project and deliver a fully automated pipeline within the desired timeframe.