Senior Data Analyst

AssetMark Financial Holdings; Charlotte (NC); Hybrid; USD 90,000 - 130,000; Full time

Benefits offered by this job

Hybrid work schedule

Job summary

AssetMark Financial Holdings seeks a Senior Data Analyst to translate business needs into scalable analytics and data products. This role designs complex dashboards, semantic models, and self-service analytics while bridging Analytics and Analytics Engineering during the Snowflake migration.

The position supports a hybrid work schedule near Charlotte, NC, and offers opportunities to mentor teams, improve data quality, and implement AI-assisted tooling to boost development efficiency and business

Qualifications

• 5+ years in analytics, BI, analytics engineering, or related data roles with leadership in requirements gathering, solution development, and data migration.
• Bachelor's or Master's degree in Analytics, Statistics, Computer Science, or Business.
• Advanced proficiency in SQL, Snowflake, and dbt.
• Experience designing dashboards with Power BI or equivalent.
• Experience migrating analytics workloads from legacy platforms to curated cloud data models.

Responsibilities

• Lead requirements gathering and translate business needs into technical specifications for analytics solutions and data products.
• Design complex dashboards, semantic models, and scalable self-service analytics.
• Partner with Analytics Engineering to define and develop canonical models and gold-layer datasets in Snowflake, including SQL/dbt transformations and data quality controls.
• Identify and implement AI-assisted tools and automation to improve efficiency, documentation, testing, migration, data quality, and user support.
• Lead migration of dashboards and analytical assets to Snowflake views through source mapping and validation.
• Evaluate new BI and analytics engineering capabilities and establish best practices for scalable architecture and data modeling.
• Provide technical mentorship and strengthen the Analytics community of practice.
• Manage solution development and migration projects coordinating stakeholders to ensure timely delivery.
• Drive adoption and measure data quality, usage, and business impact.

Skills

SQL

Snowflake

dbt

ELT

Data modeling

Data quality

Power BI

Analytics engineering

Education

Bachelor's or Master's in Analytics/CS/Statistics/Business

Tools

Git

SQL tools

Job description

Job Description:

AssetMark is a leading wealth management platform dedicated to empowering independent financial advisors. AssetMark's mission is to enable financial advisors to make a profound difference in the lives of their clients. Over 10,000 advisors partner with AssetMark for our investment offerings, innovative technology, advanced services, and expertise, which they use to delight their clients and grow their businesses. We are an integrated team of technologists, investment professionals, and operations experts working to help our clients stay at the pioneering front of wealth management.

The Job/What You'll Do:

The Senior Data Analyst leads requirements gathering and translates business needs into scalable analytics and data solutions. This role designs complex dashboards and self-service analytics while serving as a bridge between Analytics and Analytics Engineering during AssetMark's transition to Snowflake. The Senior Data Analyst partners with Analytics Engineering to develop and validate canonical models and gold-layer curated datasets, leads migration of existing analytical solutions from legacy data sources, and builds team capability through standards, mentoring, training, and reusable development patterns. The role also identifies and responsibly implements AI-assisted tools and automation to improve development efficiency, documentation, testing, data quality, and support. This role manages delivery and ensures solutions are accurate, adopted, and drive business impact.

We can consider candidates for this position who are able to accommodate a hybrid work schedule and are close to our Charlotte, NC office.

Key Responsibilities

• Lead requirements gathering and translate business needs into technical specifications for analytics solutions and data products.


• Design complex dashboards, semantic models, and scalable self-service analytics that meet user needs and functional requirements.


• Partner with Analytics Engineering to define and develop canonical models and gold-layer curated datasets in Snowflake, including SQL and dbt transformations, tests, documentation, and data quality controls.


• Identify and responsibly implement approved AI-assisted tools and automation to improve efficiency in SQL and dbt development, documentation, testing, migration, data quality, and user support while maintaining human review, security, and data governance.


• Lead migration of dashboards, semantic models, and other analytical assets to curated Snowflake views through source mapping, reconciliation, validation, and controlled retirement of legacy dependencies.


• Evaluate new BI and analytics engineering capabilities, optimize performance, and establish best practices for scalable architecture, data modeling, query design, testing, documentation, and dashboard UI/UX.


• Provide technical mentorship and strengthen the Analytics community of practice through training, code reviews, reusable patterns, and standards for Snowflake, dbt, analytics engineering, and responsible AI-assisted workflows.


• Manage solution development and migration projects by coordinating business stakeholders, analysts, data engineers, and architects to ensure timely delivery.


• Drive adoption and measure data quality, solution usage, and business impact to inform future development priorities.

Knowledge, Skills & Abilities:

• Advanced proficiency in SQL, Snowflake, and dbt, with strong knowledge of data engineering and analytics engineering practices, including ELT, dimensional modeling, testing, lineage, and data quality.


• Proven experience designing, launching, and maintaining advanced analytical solutions and self-service BI products using Power BI or comparable platforms.


• Experience migrating analytical workloads from legacy platforms to curated cloud data models using source-to-target mapping, reconciliation, Git-based version control, and code review practices.


• Demonstrated experience applying AI-assisted analytics or development tools to improve efficiency, quality, or scalability, with sound judgment around output validation, data privacy, security, and responsible use.


• Strong partnering, communication, stakeholder management, and technical mentoring skills across business, Analytics, and Data Engineering teams.

Education & Experience:

• 5+ years in analytics, BI, analytics engineering, or related data roles, with experience leading requirements gathering, solution development, and data migration projects.


• Bachelor's or Master's degree in Analytics, Statistics, Computer Science, Business,