Senior Business Analyst

POSITION SUMMARY:
The Senior Business Analyst – Data Engineering analyzes the data requirements and technical needs of the Company's most complex functional business areas within ***, providing recommendations on data solutions, architecture decisions, and data strategy. As the liaison between business stakeholders and the Data Platforms team, the Senior Business Analyst ensures that data initiative scope, data lineage, transformation logic, and analytics requirements are clearly documented, communicated, and validated.

This role works closely with data engineers and architects to design, develop, document, test and validate data solutions that meet business requirements while maintaining medallion architecture principles. The successful candidate will lead data platform innovations, mentor other analysts, and contribute technical expertise to advance our data capabilities.

PRINCIPAL RESPONSIBILITIES:
Act as a liaison with business stakeholders to analyze data requirements, reporting needs, and analytical use cases while ensuring data quality standards and architectural governance.
Create detailed technical documentation including:
Data Requirements Specifications, Logical and Physical Data Models, ETL/ELT Process Flow Diagrams, Data Lineage Maps, Transformation Rules, and Data Quality Frameworks
Design and document medallion architecture implementation (Bronze/Silver/Gold layers) for large-scale transformation projects, ensuring scalability and maintainability
Leverage AI and machine learning tools to enhance data definitions, automated table attribute analysis, and data discovery processes
Perform comprehensive data profiling, quality assessment, and source system analysis to inform data transformation strategies
Lead feasibility studies and impact analysis for proposed data platform initiatives, including cost-benefit analysis and ROI modeling
Collaborate with data engineers and architects to define technical requirements, data governance policies, and transformation standards
Provide technical guidance throughout the development lifecycle, including requirements validation, design reviews, and testing support
Build and maintain relationships with technology vendors, platform partners, and implementation specialists specializing in data technologies
Mentor and guide other business analysts and junior team members on data engineering best practices and complex analytical problem-solving
Contribute to innovation initiatives for the Data Platforms team, staying current with emerging data technologies and methodologies
Develop comprehensive implementation and knowledge transfer documentation for data solutions
Responsible for status reporting, stakeholder communication, and project coordination for data initiatives
Performs other duties as assigned

MINIMUM QUALIFICATIONS:
Bachelor's degree in Computer Science, Information Systems, Data Science, Statistics, Engineering, or a related field, OR minimum of 6 years of direct work experience in data analysis, business analysis, or data engineering roles involving complex data systems, ETL/ELT processes, or data platform development
Demonstrated experience with SQL and data transformation logic
Strong technical foundation with experience in large-scale data projects or data warehouse/lake environments

PREFERRED QUALIFICATIONS:

Experience with medallion architecture (Bronze/Silver/Gold layers) or similar data layering patterns.
Proficiency in data modeling tools and methodologies (Dimensional, Entity-Relationship modeling, etc.)

Experience with cloud data platforms (Snowflake, Databricks, Big Query, or Azure Synapse)
Hands-on experience with ETL/ELT tools and orchestration platforms (dbt, Apache Airflow, Informatica, etc.)
Knowledge of data governance frameworks and data quality best practices
Experience leveraging AI/ML for data cataloging, metadata management, or automated data profiling
Familiarity with modern data stack tools and practices
Business Analysis or Data Engineering certification (CBAP, ECBA, AWS Data Engineer, Snowflake certification)
Experience leading or architecting large-scale data transformation initiatives
Background in software development or systems engineering with transition to data platforms