Analytics Engineer

Position Summary

The Analytics Engineer is responsible for owning the design build and ongoing maintenance of data products in the MART layer of the firms data platform. This role creates and evolves foundational and business data products from governed underlying data applying reusable business logic documentation testing and access controls so data can be consumed consistently across the enterprise. The ideal candidate also authors and maintains semantic models that make trusted data easier to use for AI experiences dashboards reporting and downstream integrations into operational platforms. Success in this role requires strong technical depth a product mindset and close partnership with engineering BI analytics and business stakeholders.

Primary Responsibilities

• Own the design development and maintenance of MART-layer foundational and business data products built from curated enterprise data.
  

• Translate business requirements into reusable data products metrics and transformation logic that support consistent consumption across teams and platforms.
  

• Build and maintain semantic models with rich metadata business definitions and synonyms to enable trusted self-service analytics and AI consumption.
  

• Develop models that support multiple consumption patterns including dashboards reports AI agents APIs file delivery and operational system integrations.
  

• Apply complex business logic in a governed version-controlled manner using modern transformation tooling and software engineering best practices.
  

• Partner with data engineers BI engineers analysts architects and business stakeholders to define product intent validate logic and prioritize enhancements.
  

• Ensure data product quality through testing monitoring reconciliation and issue resolution across upstream data transformations and downstream consumption.
  

• Document data products semantic models lineage and usage guidance to improve transparency stewardship and user adoption.
  

• Support governed access patterns through metadata role-based access considerations and alignment with enterprise data governance standards.
  

• Continuously improve MART-layer patterns semantic model design and consumer enablement based on platform evolution and business needs.
  

Required Skills

• Strong experience building analytics-ready data models and reusable business logic in modern cloud data platforms such as Snowflake.
  

• Hands-on expertise with dbt or similar transformation frameworks including modular modeling testing documentation and version control.
  

• Proven ability to design and maintain semantic models metrics dimensions and business definitions for consistent downstream consumption.
  

• Strong SQL skills and experience optimizing transformation logic for performance scalability and maintainability.
  

• Experience supporting multiple data consumption patterns including BI dashboards AI use cases reporting APIs file delivery and operational integrations.
  

• Understanding of data governance metadata lineage role-based access and quality controls in enterprise data platforms.
  

• Ability to partner effectively with cross-functional stakeholders to translate business needs into scalable trusted data products.
  

• Strong written and verbal communication skills with the ability to document logic definitions assumptions and usage guidance clearly.
  

Qualifications

• Bachelors degree in Computer Science Information Systems Data Analytics Engineering or a related field or equivalent practical experience.
  

• 5 years of experience in analytics engineering data engineering BI engineering or a closely related data role.
  

• Experience building governed data models and data products in enterprise environments with multiple downstream consumers.
  

• Demonstrated experience applying software engineering best practices to analytics workflows including Git-based development testing and deployment discipline.
  

• Experience working with modern BI and semantic technologies such as Power BI Snowflake semantic capabilities or similar platforms is preferred.
  

• Familiarity with metadata/catalog platforms lineage tooling and enterprise documentation practices is preferred.
  

• Experience in financial services wealth management or other regulated industries is a plus.
  

• Demonstrated ability to work independently manage priorities and take ownership of data products from design through ongoing support