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- Tasks: Scrape and process data from various sources using Python and other tools.
- Company: Join a dynamic team focused on innovative data solutions.
- Benefits: Competitive salary, flexible hours, and opportunities for skill development.
- Why this job: Make an impact by optimising data collection and enhancing business insights.
- Qualifications: Experience in data scraping and proficiency in Python required.
- Other info: Collaborative environment with room for growth and learning.
The predicted salary is between 30000 - 42000 £ per year.
Key Responsibilities
- Data Scraping and Collection
- Gather procurement requirements from target markets by writing scripts (Python, JavaScript, etc.) or using tools.
- Collect enterprise information, product details, and trade data from multiple sources (websites, APIs, databases, etc.).
- Maintain and optimize data scraping scripts to ensure efficiency and stability.
- Handle anti-scraping mechanisms to ensure data collection compliance.
- Data Cleaning and Processing
- Clean and format the raw scraped data.
- Identify and remove duplicate and invalid data.
- Standardize data formats (country, city, category, HS code, etc.).
- Process multilingual data (Chinese, English, Japanese, Thai, etc.).
- Data Review and Screening
- Verify the authenticity and validity of procurement requirements according to platform standards.
- Verify the accuracy and completeness of enterprise information.
- Screen high-quality data that meets platform requirements.
- Identify and flag suspicious or low-quality data.
- Data Entry and Management
- Store the approved data in the platform database.
- Maintain the data classification and labeling system.
- Manage data versions and update records.
- Ensure the accuracy and completeness of data entry.
- Data Quality Monitoring
- Regularly check data quality metrics (completeness, accuracy, timeliness, etc.).
- Monitor the execution status of data scraping tasks.
- Identify and resolve data quality issues.
- Generate data quality reports.
- Tool Development and Optimization
- Develop or optimize data scraping tools and scripts.
- Establish data review workflows and standards.
- Enhance the automation level of data processing.
- Optimize data processing efficiency.
- Target Market Research
- Research data sources and acquisition channels in target markets.
- Understand the data characteristics and formats of different markets.
- Identify new data collection opportunities.
- Monitor market changes and adjust data collection strategies.
Job Requirements
- Educational Background
- Bachelor’s degree or above in Computer Science, Data Science, Information Technology, or related fields.
- Work Experience
- 1-3 years of experience in data scraping, data processing, or data analysis.
- Experience in web scraping development is preferred.
- Experience in data cleaning and auditing is preferred.
- Experience in B2B platforms or trade data is preferred.
- Candidates with cross-border trade industry background are preferred.
- Technical Skills
- Programming Languages: Proficient in Python (required); familiarity with JavaScript, Java, etc. is preferred.
- Web Scraping Frameworks: Familiar with Scrapy, BeautifulSoup, Selenium, Playwright, and other scraping tools.
- Data Processing: Familiar with Pandas, NumPy, and other data processing libraries.
- Database: Familiar with MySQL, PostgreSQL, MongoDB, and other database operations.
- API: Understanding of RESTful API and JSON data processing.
- Tools: Familiar with Git version control, Jupyter Notebook, and other development tools.
- Regular Expressions: Able to use regular expressions for text matching and processing.
- Multilingual Processing: Experience in multilingual text processing (Chinese, English, Japanese, Thai, etc.) is preferred.
- Business Skills
- Understanding of B2B cross-border trade business processes.
- Familiar with the data structure of Request for Quotation (RFQ).
- Understanding of trade-related concepts such as company information, product categories, and HS codes.
- Capable of assessing the authenticity and validity of data.
- Soft Skills
- Fluent in English and Mandarin (spoken and written).
- Detail-oriented and meticulous, capable of handling large volumes of repetitive tasks.
- Excellent problem-solving skills and logical thinking.
- Strong learning ability and adaptability.
- Capable of working under pressure and completing tasks on time.
- Strong teamwork spirit.
- Nice to Have
- Project experience with web scraping frameworks such as Scrapy and Selenium.
- Experience in data cleaning and ETL.
- Understanding of machine learning or natural language processing.
- Proficient in Docker and Linux systems.
- Experience in data visualization (Tableau, Power BI, etc.).
Please send your resume to hr.zhimao@gmail.com
Data Engineer (Web Scraping) employer: ACROMETA LIFESTYLE PTE. LTD.
Contact Detail:
ACROMETA LIFESTYLE PTE. LTD. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Web Scraping)
✨Tip Number 1
Network like a pro! Reach out to folks in the industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your web scraping projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common data engineering questions. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love hearing from passionate candidates like you!
We think you need these skills to ace Data Engineer (Web Scraping)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data scraping and processing. Use keywords from the job description to show we’re on the same page about what you bring to the table.
Show Off Your Skills: Don’t just list your programming languages; give us examples of how you've used Python or JavaScript in real projects. We love seeing practical applications of your skills!
Be Clear and Concise: When writing your cover letter, keep it straightforward. We appreciate clarity, so get to the point about why you’re a great fit for the Data Engineer role without fluff.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss any important updates from us!
How to prepare for a job interview at ACROMETA LIFESTYLE PTE. LTD.
✨Know Your Tech Stack
Make sure you’re well-versed in the programming languages and tools mentioned in the job description, especially Python. Brush up on your knowledge of web scraping frameworks like Scrapy and BeautifulSoup, as well as data processing libraries like Pandas. Being able to discuss your experience with these tools will show that you're ready to hit the ground running.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in data scraping or processing. Think of examples where you had to handle anti-scraping mechanisms or clean messy data. This will demonstrate your analytical thinking and ability to tackle real-world problems, which is crucial for this role.
✨Understand the Business Context
Familiarise yourself with B2B cross-border trade processes and the importance of accurate data in this context. Be ready to explain how your technical skills can contribute to the company’s goals. Showing that you understand the bigger picture will set you apart from other candidates.
✨Prepare for Multilingual Challenges
Since the role involves processing multilingual data, be prepared to discuss any relevant experience you have with languages like Mandarin, Japanese, or Thai. If you’ve worked with multilingual datasets before, share those experiences to highlight your adaptability and attention to detail.
