Associate Data Engineer

AssetMark•Charlotte, NC

2d•$95,000 - $105,000•Hybrid

About The Position

AssetMark is a leading strategic provider of innovative investment and consulting solutions serving independent financial advisors. We provide investment, relationship, and practice management solutions that advisors use in helping clients achieve wealth, independence, and purpose. The Job/What You'll Do: The Associate Data Engineer is an integral member of the Data Team, responsible for helping to transform raw data into reliable, easy-to-use datasets for analysts, data scientists, and business users. You'll apply software engineering best practices to analytics code and focus on building foundational data models. This role provides an excellent opportunity to grow technical expertise in data modeling and the modern data stack. We can consider candidates for this position who are able to accommodate a hybrid work schedule and are close to our Charlotte, NC office.

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).
Familiarity with version control systems (e.g., Git).
Experience with a BI/data visualization tool (e.g., Tableau, Looker, Power BI).
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.
A positive and solution-oriented mindset, with comfort working in an agile environment.
Self-motivated with strong task organizational skills and a desire to learn new technologies and methodologies.
1+ years of experience in a data-focused role (e.g., Data Analyst, BI Analyst, or equivalent experience).

Nice To Haves

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.

Responsibilities

Data Modeling & Transformation 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.
Data Quality & Governance Implement basic data quality checks and automated tests for new and existing data models.
Support efforts to ensure data integrity and reliability.
Documentation & Collaboration Draft and maintain documentation (e.g., data catalogs, ReadMEs) for new datasets and transformation processes to promote self-service and data understanding.
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.
Technical Operations Follow and advocate for the team's internal standards for code style, maintainability, and best practices.
Use version control (Git) and participate in code reviews for data model changes.
Provide support and basic training to users of data sets and dashboards.