AssetMark is looking to transform raw data into reliable, easy-to-use datasets for analysts, data scientists, and business users by building foundational data models and applying software engineering best practices to analytics code.
Requirements
- Solid proficiency in SQL (Structured Query Language).
- Familiarity with data transformation tools, preferably dbt (data build tool).
- Understanding of data warehousing concepts (e.g., dimensional modeling/Kimball).
- Experience with a major cloud data warehouse platform (e.g., Snowflake, Google BigQuery, Redshift) is a plus.
- Basic knowledge of a scripting language like Python for data-related tasks is beneficial.
- Familiarity with version control systems (e.g., Git).
- Experience with a BI/data visualization tool (e.g., Tableau, Looker, Power BI).
Responsibilities
- Develop and test data models, primarily using SQL and dbt, as assigned by more senior Analytics Engineers.
- Write and maintain data transformation logic to clean, organize, and structure data for analysis.
- Contribute to the design and extension of the Enterprise Dimensional Model for small, defined sections.
- Implement basic data quality checks and automated tests for new and existing data models.
- Support efforts to ensure data integrity and reliability.
- Draft and maintain documentation (e.g., data catalogs, ReadMEs) for new datasets and transformation processes to promote self-service and data understanding.
- Use version control (Git) and participate in code reviews for data model changes.
Other
- We can consider candidates for this position who are able to accommodate a hybrid work schedule and are close to our Charlotte, NC office.
- Collaborate with Data Analysts to understand and address their data needs for reporting and analysis.
- Work with Data Engineers to understand data sources and ingestion processes.
- Follow and advocate for the team's internal standards for code style, maintainability, and best practices.
- Provide support and basic training to users of data sets and dashboards.
- Excellent communication skills with the ability to clearly articulate technical concepts and requirements to both technical and non-technical stakeholders.
- Problem-solving and critical thinking skills to investigate and resolve data issues.
