Data & AI Specialist - Data Scraping, Enrichment & Quality Assurance

Overview

project-based role

full-time contract

Key Responsibilities

• Data Acquisition & Scraping
• Design, develop, and maintain scalable web-scraping systems and APIs to collect structured and unstructured data from diverse sources.
• Ensure compliance with data privacy laws (GDPR, CCPA) and site-specific terms of service.
• Data Enrichment & Transformation
• Implement pipelines to clean, normalize, and enrich raw data using third-party datasets, NLP (natural language processing), and machine learning techniques.
• Build automated matching and deduplication processes to maintain a unified source of truth.
• Quality Assurance & Monitoring
• Create automated QA checks to validate data accuracy, completeness, and consistency.
• Set up monitoring and alert systems to catch anomalies or pipeline failures early.
• AI & Process Optimization
• Integrate AI models for entity extraction, text classification, and predictive enrichment.
• Work with the data science team to design features that feed analytics and machine learning models.
• Collaboration & Documentation
• Partner with product, engineering, and analytics teams to define data requirements and priorities.
• Maintain clear technical documentation and data lineage records
  

Requirements

• Strong programming skills in Python (Scrapy, BeautifulSoup, Selenium, Playwright) or equivalent languages.
• Experience with data pipelines and ETL tools (Airflow, Prefect, or similar).
• Proficiency in SQL/NoSQL databases and data warehousing (e.g., BigQuery, Snowflake).
• Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker/Kubernetes).
• Knowledge of machine learning workflows and libraries (scikit-learn, spaCy, Hugging Face) is a big plus.
• Solid understanding of data privacy and ethical data collection practices.
  

Nice-to-Have

• Experience with LLMs (large language models) for text enrichment.
• Background in data visualization or BI tools (Tableau, Looker, Power BI).
• Familiarity with real-time streaming data (Kafka, Kinesis).
  

Traits for Success

• Detail-oriented with a knack for spotting hidden data issues.
• Curious problem solver who loves automation and efficiency.
• Comfortable in a fast-paced environment where requirements evolve quickly
  

Benefits