Senior Snowflake Data Engineer

Roles and Responsibilities:

• Requirements Elucidation:

  Liaise effectively with coworkers and clients to clearly understand the requirements for each data engineering task.

• Infrastructure Design & Generation:

  Conceptualize and generate robust infrastructure that facilitates the access and analysis of big data, primarily utilizing

  Snowflake

  .

• Framework Optimization:

  Reformulate existing data frameworks and pipelines to optimize their functioning, ensuring efficiency and scalability.

• Testing & Validation:

  Rigorously test data structures and pipelines to ensure they are fit for use, meet performance criteria, and deliver accurate results.

• Data Preparation:

  Prepare raw data for manipulation and analysis by data scientists, ensuring data quality and readiness.

• Error Detection & Correction:

  Proactively detect and correct errors within data processes and pipelines, maintaining data integrity.

• Data Accessibility & Backup:

  Ensure that all work, including data pipelines and processed data, remains backed up and readily accessible to relevant coworkers.

• Continuous Learning:

  Remain up-to-date with industry standards and technological advancements, particularly within the

  Snowflake

  ecosystem, to continuously improve the quality of outputs.

Required Skills:

• Strong proficiency in

  Snowflake

  for data warehousing and engineering.
• Ability to conceptualize and generate big data infrastructure.
• Skills in optimizing existing data frameworks.
• Proficiency in testing data structures and pipelines.
• Aptitude for preparing raw data for analysis.
• Strong error detection and correction abilities.
• Knowledge of data backup and accessibility best practices.
• Commitment to staying updated with industry standards and technological advancements.
• Excellent communication skills for liaising with coworkers and clients.
• Strong analytical and problem-solving skills for data-related challenges.