Organizes, updates, and maintains gathered data that will aid in making the data actionable
Demonstrates basic knowledge of the data system components to determine controls needed to ensure secure data access
Be responsible for making custom configuration changes in one to two tools to generate a product at the business or customer request
Updates logical or physical data models based on new use cases with minimal supervision
Adds to team culture of diversity, equity, inclusion, and respect
Required qualifications, capabilities, and skills
Formal training or certification on Data engineering concepts and 2+ years applied experience
Proven experience managing the full lifecycle of data, from collection and storage to analysis.
Proficiency in Python for data manipulation and analysis.
Proficiency with major cloud platforms such as AWS and Snowflake. Familiarity with ETL tools, including Spark and Databricks.
Extensive knowledge of database management systems and data modelling. Understanding of SQL and NoSQL database concepts.
Knowledge of Data Mesh, data modeling, and domain-driven design. Experience with version control systems and tools, including Git, GitHub, GitLab, and Bitbucket.
Demonstrated ability in statistical data analysis, selecting appropriate tools and identifying relevant data patterns for comprehensive analysis.
Experience implementing custom changes in tools to produce tailored data products.