How You’ll Spend Your Day

·    Lead business analysis activities for the migration of the existing People Analytics HRBI data platform from Oracle on-premises to Azure Databricks.

·    Analyze the existing ETL processes, database objects, data models, transformation logic, dependencies, schedules, controls, and operational procedures.

·    Work with HR data owners, subject-matter experts, technical teams, and architects to clarify and document the required behavior of the target data solution.

·    Decompose the current HRBI solution into data domains and define the detailed migration scope for the assigned domains.

·    Create and maintain business requirements, functional specifications, user stories, acceptance criteria, data dictionaries, and source-to-target mappings.

·    Document current-state and target-state data flows, including source systems, ingestion processes, transformation rules, database entities, and downstream data interfaces.

·    Identify the facts, dimensions, history, calculations, business rules, and shared Core HR elements required for each migrated domain.

·    Ensure that existing HRBI logic is fully understood and documented before it is rebuilt or adapted in Azure Databricks.

·    Work closely with Data Engineers to translate business and data requirements into implementable ETL and database development tasks.

·    Support the definition and review of target data models, database structures, data layers, naming conventions, and reusable data-processing patterns.

·    Define data-quality checks, reconciliation rules, control totals, and acceptance thresholds for migrated data.

·    Prepare test scenarios and expected results for data ingestion, transformation, history, data quality, and reconciliation.

·    Support System Integration Testing, User Acceptance Testing, defect analysis, and validation of migrated ETL processes and database outputs.

·    Analyze data differences between the Oracle HRBI solution and Azure Databricks, coordinate root-cause analysis, and follow issues through resolution.

·    Identify cross-domain dependencies, sequencing constraints, migration risks, and required prerequisites.

·    Support domain cutover planning, parallel-run activities, production-readiness reviews, and controlled retirement of migrated Oracle ETL and database components.

·    Maintain the domain backlog, track open requirements and decisions, and provide clear status updates on progress, risks, issues, and blockers.

·    Work independently across assigned domains while collaborating effectively with the second Business Analyst and the wider delivery team.

Your Qualification and Experience

·    Experience in the pharmaceutical or manufacturing industry, combined with hands-on experience in AI, is required.

·    Bachelor’s degree in Information Systems, Computer Science, Industrial Engineering, Business Administration, or equivalent relevant experience.

·    Minimum 5 years of experience as a Business Analyst in data warehouse, ETL, data lake, database migration, or enterprise data-platform projects.

·    Proven experience analyzing complex ETL processes, relational databases, data models, transformation logic, and data dependencies.

·    Experience preparing functional specifications, source-to-target mappings, data dictionaries, user stories, test scenarios, and acceptance criteria.

·    Experience supporting data migration, data validation, reconciliation, SIT, UAT, and production cutover activities.

·    Experience working with cross-functional teams including business stakeholders, data engineers, data architects, database specialists, QA, platform teams, Security, and Data Privacy.

·    Experience in HR, HRBI, People Analytics, SuccessFactors, or other Human Capital Management data domains is preferred.

Skills and Capabilities

·    Strong business analysis skills with the ability to translate business processes and legacy-system behavior into precise data and ETL requirements.

·    Strong understanding of ETL/ELT concepts, relational databases, data warehousing, data lakes, facts, dimensions, history management, and data lineage.

·    Ability to read and analyze SQL, database schemas, mapping documents, ETL specifications, and technical data-flow documentation.

·    Practical SQL skills for data analysis, profiling, validation, reconciliation, and investigation of data defects.

·    Experience with source-to-target mapping and documentation of cleansing, derivation, transformation, aggregation, and validation rules.

·    Ability to analyze large and complex legacy solutions, identify undocumented logic, and structure requirements by data domain and migration wave.

·    Understanding of data-quality principles, reconciliation methods, control totals, exception handling, and auditability.

·    Familiarity with Azure Databricks, Azure Data Factory, Delta Lake, Medallion Architecture, and cloud data-platform concepts is preferred.

·    Ability to facilitate requirement workshops and communicate effectively with both business and technical stakeholders.

·    Strong analytical, problem-solving, documentation, prioritization, and decision-tracking capabilities.

·    Ability to manage multiple domains or workstreams simultaneously and collaborate closely with another Business Analyst.

·    High attention to detail and commitment to ensuring that migrated data and business logic remain accurate, complete, and traceable.