Key Responsibilities

1. Perform web scraping using Python tools like BeautifulSoup, Requests, Selenium, or Scrapy.
2. Build automated scripts to extract data from websites, directories, and APIs.
3. Clean, transform, and validate data to ensure accuracy and consistency.
4. Store and manage scraped data using CSV, Excel, SQL, or cloud databases.
5. Analyze datasets to identify patterns, trends, and insights.
6. Prepare dashboards, reports, and visualizations to support business decisions.
7. Collaborate with the Sales team to generate and qualify business leads.
8. Maintain documentation for data sources, scripts, and processes.
9. Stay updated with web scraping standards, anti-bot handling, and ethical guidelines.

Required Skills

1. Strong knowledge of Python programming.
2. Hands-on experience with web scraping tools
3. Experience with pandas and NumPy for data cleaning and analysis.
4. Understanding of HTML structure, XPaths, and CSS selectors.
5. Familiarity with SQL for data querying (preferred).
6. Basic knowledge of Excel or Google Sheets.
7. Problem-solving and logical thinking skills.
8. Ability to handle large datasets.

Nice-to-Have Skills

1. Experience with APIs and JSON data handling.
2. Knowledge of data visualization tools (Tableau, Power BI, Matplotlib, Seaborn).
3. Understanding of automation and scheduling tools (Cron jobs, Python schedulers).
4. Basic understanding of machine learning concepts.

Qualifications

1. Bachelor’s degree in Computer Science, IT, Engineering, Data Science, Mathematics, or related field.
2. Completed courses or projects in Python and data analytics.
3. Web scraping project experience (personal or academic) is a strong plus.

What We Offer

1. Opportunity to work on real-world data challenges.
2. Exposure to sales data and business growth strategies.
3. Friendly and collaborative team environment.
4. Career growth in data engineering, analytics, or automation.