At Ceartas, we lead the way in AI-powered brand protection, copyright law, and digital security,
safeguarding the integrity of content creators, brands, and enterprises worldwide. As we scale
rapidly, we're looking for a Data & Python Software engineer to drive innovation in our data
pipelines and crawling technologies. In this pivotal role, you'll collaborate with our CTO and
Head of Engineering, steering our Data Engineering Team toward developing groundbreaking
solutions for digital security challenges.
Build Scalable Web Data Extraction Pipelines:
Design and develop web scraping systems that support large-scale web data extraction and
brand protection workflows. Ensure that data moves reliably from collection through processing to storage while maintaining performance, resilience, and operational stability at scale.
Ensure Data Quality and Governance:
Own data validation, consistency, and governance across ingestion, storage, and serving layers.
Establish clear standards for schema design, transformation logic, and monitoring to guarantee
trustworthy, production-grade datasets that can be reliably consumed across the organization.
Optimize Performance and Reliability:
Continuously improve scraping system efficiency through performance tuning, cost optimization, and architectural enhancements. Implement logging, metrics, and tracing to monitor production systems, diagnose issues quickly, and maintain high reliability under growing workloads.
Responsibilities:
Design, build, and maintain high-performance web scraping systems as well backend services and data pipelines supporting web data extraction and brand protection use cases
Implement and maintain scraping focused APIs and other data services that power internal products and external integrations
Build reliable ingestion, processing, and storage workflows for large-scale web data
Handle cleaning of web data and ensure data quality, validation, and governance across ingestion, storage, and serving layers
Optimize scraping systems for performance, scalability, reliability, and cost efficiency
Monitor, debug, and improve scraping system reliability using observability tools (logging, metrics, tracing)
Collaborate closely with product and engineering teams to deliver features from design through full end-to-end production deployment
Take independent ownership of systems in production, including maintenance,
iteration and performance management
Core Technical Requirements:
Experience with web scraping
Strong SQL skills
Strong Python experience
Experience with PostgreSQL or similar relational databases
Experience designing and building scalable APIs and backend services (e.g. FastAPI, Django, or similar frameworks)
Experience designing efficient, scalable data models and database schemas
Hands-on experience deploying and operating systems in the cloud (AWS, GCP, or Azure)
Experience working with Docker and containerized environments
Preferred Technical Requirements:
Experience with workflow orchestration tools such as Airflow
Experience with browser-based automation tools (Playwright, Selenium, or similar)
Experience with DBT or analytics-focused data transformation workflows
Experience building or operating high-concurrency systems and task queues
Experience designing and deploying cloud-native workflows on AWS
Familiarity with CI/CD pipelines and production deployment practices
Experience working in a high-growth, early-stage startup environment
Experience - University education in a technical field such as Computer Science, Engineering or similar. Masters level preferred. 4+ years ( or 2 year+ in a early stage startup)
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