
Building Scalable Data Pipelines
7 days ago
Data engineers design, build, and maintain robust data pipelines to extract insights from structured and unstructured data. This role requires expertise in machine learning life cycles, data mining, and ETL techniques.
- Key Responsibilities:
- Create scalable data pipelines for high-quality data
- Collaborate with cross-functional teams to meet business needs
- Maintain tools and libraries used by multiple teams across the organization
About Us:
This is a pivotal role that drives business success through data-driven decisions. We are seeking an experienced professional with hands-on experience in Cloud Data Warehousing platforms such as Redshift, Snowflake, or Databricks SQL, and proficiency in software development lifecycle and software engineering practices.
- Qualifications:
- Bachelor's or master's degree in Computer Science, Data Science, Engineering, or a related field
- Minimum 3 years of experience in working with Python, SQL, PySpark, and bash scripts
- Familiarity with commonly used machine learning libraries such as scikit-learn and xgboost
- Hands-on experience with CI/CD tools, version control, and orchestration
What We Offer:
The selected candidate will have opportunities for growth, collaboration with experienced professionals, and a dynamic work environment. They will be responsible for designing, building, and maintaining scalable data pipelines, ensuring high-quality data, and collaborating with cross-functional teams to meet business needs.
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