Python Data Engineer

Description:

Cognilium.ai is looking for an enthusiastic Python Data Engineer with 0–1 year of experience to join their team. This is an excellent opportunity for someone early in their career to gain hands-on experience in data engineering, working on real-world tasks involving APIs, web scraping, databases, and containerized deployments. You'll have the chance to work with Linux servers, cloud platforms, and build reliable, scalable data pipelines.

Key Responsibilities:

• Write Python scripts to extract, clean, and transform data from web sources and APIs.

• Develop and maintain web scraping solutions using tools like BeautifulSoup, Scrapy, or Selenium.

• Build and manage lightweight ETL/data pipelines.

• Work with APIs for data ingestion and automation.

• Interact with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB) to store and query data.

• Package applications using Docker for deployment and reproducibility.

• Work with Linux-based servers to run, monitor, and troubleshoot jobs.

• Collaborate with team members to ensure data quality and efficient workflows.

• Deploy and test solutions on cloud environments like AWS, GCP, or Azure.

Qualifications:

• Strong foundation in Python.

• Basic understanding of RESTful APIs – consuming and integrating APIs.

• Experience or familiarity with web scraping libraries (e.g., BeautifulSoup, Scrapy, Requests).

• Understanding of SQL and at least one database system (e.g., MySQL, PostgreSQL).

• Familiarity with Docker and containerization concepts.

• Comfortable working in Linux command-line environments.

• Good problem-solving skills and willingness to learn.

• Clear communication and ability to document work.

Bonus Points (Nice to Have):

• Familiarity with cloud services (e.g., EC2, Lambda, S3, GCS).

• Experience with Git/GitHub for version control.

• Exposure to task schedulers (like cron or Airflow).

• Understanding of basic networking concepts.

What We Offer:

• Opportunity to work on real-world data projects from day one.

• Supportive learning environment with mentoring and code reviews.

• Access to cloud and container tech stacks.

• Flexible work hours and remote-friendly culture.

• A chance to grow into a full-stack data engineering role.