Senior Data & Python Software Engineer

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., * 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

• 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)