The Analytics Engineer II builds and delivers enterprise data products that support analytical and operational reporting across Mariner. This role translates defined business requirements into scalable data models and datasets in Snowflake using SQL, dbt, and Python while contributing to data quality, governance, and AI-enabled analytics capabilities. The Analytics Engineer II partners with Data Engineering, Business Intelligence, business analysts, and other stakeholders throughout the analytics lifecycle. This opportunity offers hands-on involvement in modern data platforms, semantic-layer development, and the implementation and ongoing support of data products across the organization.
Responsibilities- Collaborate with business stakeholders to gather and clarify data and reporting requirements and translate them into effective data solutions.
- Develop and maintain scalable data models and data products using dbt and Snowflake in alignment with established architecture and engineering standards.
- Partner with Data Engineering, Business Intelligence, and business teams to design and implement data products across the analytics lifecycle.
- Contribute to semantic-layer models, business metrics, and standardized definitions that support AI-enabled agents, workflows, and consistent analytics.
- Apply Snowflake capabilities, including data definition language (DDL) operations, role-based access control (RBAC), SQL functions, and Snowflake Cortex, in the development and support of data products.
- Support data quality and governance by applying data validation, security, and quality practices throughout data development and implementation.
- Participate in code reviews, version control, testing, and continuous integration and continuous delivery (CI/CD) processes in accordance with team standards.
- Provide clear project updates, technical documentation, and implementation status to technical and business stakeholders.
Requirements- 3+ years of professional experience in analytics engineering, data engineering, or business intelligence.
- 3+ years of experience with SQL and analytical databases such as Snowflake, Databricks, SQL Server, or Azure.
- Experience developing and maintaining data models, pipelines, and reporting datasets.
- Experience working in Agile environments and collaborating with cross-functional teams.
Preferred qualifications include a bachelor's degree in computer science, engineering, data analytics, or a related technical field; experience in wealth management or financial services; experience with dbt for data modeling, testing, documentation, and deployment workflows; experience with Git and version control practices; understanding of extract, load, transform (ELT) and extract, transform, load (ETL) processes and tools; and exposure to semantic-layer concepts and tools.
Skills- Apply strong analytical, problem-solving, and data validation skills to develop reliable data solutions.
- Communicate effectively with technical and business stakeholders, including providing clear documentation and project updates.
- Collaborate across Data Engineering, Business Intelligence, and business teams to deliver solutions that meet defined needs.
- Organize and coordinate work effectively across assigned projects while contributing within established engineering and delivery practices.
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