Commercial Analytics Engineer Business Decision Intelligence

Becton Dickinson Medical Devices•San Diego, CA

16h•Onsite

About The Position

The Analytics Analyst designs, builds, and maintains dashboards, reports, and semantic layer assets that enable commercial business users to access governed, accurate insights. Working within defined data products and under guidance from senior analysts and leads, this role translates business requirements into self-service BI solutions and maintains the quality and usability of the analytics user interface. The Analyst demonstrates solid foundational skills in BI tooling, semantic layer development, and stakeholder communication, representing a natural progression within the analytics job family.

Requirements

Bachelor's degree in Business Analytics, Information Systems, Computer Science, Data Science, or a related field.
1 year experience (or equivalent) in analytics, business intelligence, or a data-focused role.
Proficiency in at least one enterprise BI platform (e.g., Power BI, Tableau, Looker, Qlik).
Solid SQL skills for data querying, validation, and analysis.
Familiarity with semantic layer concepts including measures, dimensions, hierarchies, and calculated metrics.
Experience translating business requirements into reporting and dashboard solutions.
Understanding of commercial data domains such as sales pipeline, revenue, forecasting, or customer data.
Strong communication skills with the ability to explain data concepts to non-technical stakeholders

Nice To Haves

Experience with semantic layer or BI modeling tools (e.g., LookML, DAX, AtScale).
Exposure to modern cloud data platforms (e.g., Snowflake, BigQuery, Databricks).
Familiarity with data catalog or metadata management tools.
Experience in MedTech, Life Sciences, or similarly regulated industries.
Understanding of UX/UI design principles applied to data visualization.
Familiarity with AI/ML concepts, prompt engineering, or agentic workflow tooling.

Responsibilities

Build and maintain interactive dashboards and standardized reports in the enterprise BI platform (e.g., Power BI, Tableau) that address recurring commercial reporting needs.
Translate business user requirements into clear, accurate, and usable visualizations aligned to approved data models and metric definitions.
Apply consistent design standards, layout conventions, and UX best practices to ensure reports are intuitive and accessible to non-technical users.
Perform unit testing and validation of report outputs against source data to ensure accuracy before deployment.
Build and maintain semantic layer objects (e.g., measures, dimensions, hierarchies, calculated fields) within the governed BI and analytics platform.
Ensure semantic objects conform to approved business taxonomy, metric definitions, and naming conventions.
Support the discoverability of analytics assets by maintaining metadata, descriptions, and documentation within the data catalog or BI platform.
Identify and escalate inconsistencies between semantic layer definitions and source data models to senior team members.
Gather and clarify requirements from commercial business users to ensure dashboard and reporting solutions meet their analytical needs.
Provide first-line support for BI platform questions, report issues, and data interpretation queries from business users.
Assist in user acceptance testing (UAT) of new dashboards and reports with business stakeholders.
Create and maintain user guides, glossaries, and training materials to support self-service analytics adoption.
Monitor dashboard and report data freshness, flagging anomalies or stale data to the appropriate pipeline owners.
Participate in regular data quality reviews, logging issues and tracking resolution in alignment with team processes.
Support regression testing and validation when upstream data models or pipeline changes impact existing reports.
Follow team standards for version control, change management, and documentation of BI assets.
Support the development and testing of agentic AI workflows that leverage governed semantic layer assets and BI data products for automated commercial insights delivery.
Assist in annotating, labeling, and preparing training data sets drawn from commercial analytics outputs to support AI model development and fine-tuning efforts.
Participate in prompt engineering and evaluation activities for AI-assisted reporting and analytics use cases, ensuring outputs align with approved metric definitions.
Collaborate with senior analysts and Decision Science teams to validate agentic AI outputs against established BI benchmarks and data quality standards.
Document agentic AI workflows, input/output specifications, and edge cases to support model governance and continuous improvement.