Data Engineer Associate

Key Responsibilities:

• Data Pipeline Development: Assist in the design and implementation of data pipelines to extract, transform, and load (ETL) data from various sources into data warehouses or databases.
• Data Quality Assurance: Monitor and ensure the quality and integrity of data throughout the data lifecycle, identifying and resolving any data discrepancies or issues.
• Collaboration & Analysis: Work closely with data analysts, data scientists, and other stakeholders to understand data requirements and deliver solutions that meet business needs as well as perform analyses aligned to anchor domain.
• Documentation: Maintain clear and comprehensive documentation of data processes, pipeline architectures, and data models for reference and training purposes.
• Performance Optimization: Help optimize data processing workflows and improve the efficiency of existing data pipelines.
• Support Data Infrastructure: Assist in the maintenance and monitoring of data infrastructure, ensuring systems are running smoothly and efficiently.
• Learning and Development: Stay updated on industry trends and best practices in data engineering, actively seeking opportunities to learn and grow in the field.

Qualifications

• Education: Bachelor's degree in Computer Science, Data Science, Information Technology, or a related field preferred; relevant coursework or certifications in data engineering or programming is a plus.
• Technical Skills: Familiarity with programming languages such as Python or JavaScript; knowledge of SQL and experience with databases (e.g., Snowflake, MySQL, or PostgreSQL) is preferred.
• Data Tools: Exposure to data processing frameworks and tools (e.g. PBS/Torque, Slurm, or Airflow) is a plus.
• Analytical Skills: Strong analytical and problem-solving skills, with a keen attention to detail.
• Communication Skills: Excellent verbal and written communication skills, with the ability to convey technical information clearly to non-technical stakeholders.
• Team Player: Ability to work collaboratively in a team environment and contribute to group projects.
• Adaptability: Willingness to learn new technologies and adapt to changing priorities in a fast-paced environment.