0–2 years of experience in software development, data engineering, or related fields., Degree in Computer Science, Computer Engineering, Information Systems, or equivalent technical background., Proficiency in Python for data manipulation and automation., Understanding of HTML, CSS selectors, and web page structures..
Key responsabilities:
Design and maintain robust data collection pipelines from various sources.
Extract and structure information from unstructured or semi-structured formats.
Clean, filter, and validate raw data to ensure high quality and usability.
Collaborate with engineering and product teams to optimize data storage and access patterns.
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The Data Science team at TRACTIAN focuses on extracting valuable insights from vast amounts of industrial data. Using advanced statistical methods, algorithms, and data visualization techniques, this team transforms raw data into actionable intelligence that drives decision-making across engineering, product development, and operational strategies. The team constantly works on optimizing prediction models, identifying trends, and providing data-driven solutions that directly enhance the company’s operational efficiency and the quality of its products.
What you'll do
We’re looking for software and data engineers to join our newly established Data Gathering and Labeling (DGL) team. In this role, you'll be critical to building Tractian's comprehensive and diverse datasets, from industrial equipment documentation to sensor data like vibration and temperature. Your work will directly power new features in our platform and enhance our competitive advantage through richer and more reliable data resources.
Responsibilities
Design and maintain robust data collection pipelines from a wide range of sources, including websites, documents, APIs, and raw sensor data
Extract and structure information from unstructured or semi-structured formats into clean, standardized schemas
Handle real-world data challenges like pagination, rate limits, CAPTCHAs, noise, missing values, and inconsistent formatting
Clean, filter, and validate raw data to ensure high quality, consistency, and usability across our systems
Develop small tools and utilities to support and automate data collection workflows
Support the creation and maintenance of labeling pipelines for ML applications
Collaborate with engineering and product teams to optimize data storage and access patterns
Document data sources, collection methodologies, and processing procedures for reproducibility
Requirements
0–2 years of experience in software development, data engineering, or related fields
Degree in Computer Science, Computer Engineering, Information Systems, or equivalent technical background
Understanding of HTML, CSS selectors, and how web pages are structured
Strong problem-solving skills and an eye for detail
Ability to work in a fast-paced environment and manage shifting priorities
Technical Skills
Proficiency in Python, especially for data manipulation and automation
Experience (academic or professional) with data extraction using tools like `requests`, `BeautifulSoup`, or similar
Familiarity with REST APIs and the HTTP protocol
Experience with data cleaning techniques such as:
Handling missing or inconsistent values
Removing duplicates and outliers
Standardizing formats (e.g., dates, units, text normalization)
Validating data against schemas or expected ranges
(Optional) Exposure to browser automation tools like Selenium or Playwright
Nice to Have
Experience with web scraping libraries/frameworks like Scrapy, Playwright, or Selenium
Familiarity with proxy usage, headless browsers, or CAPTCHA bypass techniques
Understanding of database systems (SQL or NoSQL)
Exposure to rapid prototyping tools like Streamlit
Previous experience working with or around industrial equipment or maintenance systems
Required profile
Experience
Spoken language(s):
English
Check out the description to know which languages are mandatory.