Business Systems Analyst – Customer Data Domain

The Domain-Driven Business Systems Analyst, specializing in the Customer Data Domain is a critical role blending deep business acumen with advanced technical expertise. This analyst significantly influences domain-specific logic modeling, integrates sophisticated customer-centric analytics, and ensures technical alignment with modern data stack methodologies. Collaborating closely with product owners, data architects, and engineering teams, the analyst translates intricate business demands into precise technical requirements, enhancing customer data optimization and analytics capabilities across the enterprise.

Key Responsibilities

Domain Logic Modeling:

• Develop, enhance, and validate domain-specific logic models and entity relationship diagrams (ERD) tailored to customer data management.
• Lead workshops and technical sessions between stakeholders and engineering teams to refine logic constructs, ensuring alignment with strategic business objectives and technical feasibility.

Outside-In Technical Insights:

• Continuously monitor and integrate cutting-edge methodologies, including customer data platforms (CDP), master data management (MDM), and event-driven architecture (EDA), to inform robust internal data strategies.
• Conduct benchmarking and gap analyses against best-in-class industry practices and emerging customer analytics technologies.

Advanced Technical Guidance:

• Advise Product Owners on leveraging modern data stack capabilities, including cloud data warehouses (Snowflake, Azure Synapse), streaming technologies (Kafka, Azure Event Hubs), and API integrations for seamless customer data utilization.
• Support Product Owners in defining technical user stories, acceptance criteria, and ensuring these align strategically with advanced analytics outcomes and technical architecture standards.

Comprehensive Requirements Engineering:

• Collaborate with solution architects and developers to produce highly detailed technical specifications including data schemas, JSON payload definitions, ETL pipelines, and microservices architecture documentation.
• Precisely document user requirements into actionable technical specifications, data flow diagrams (DFDs), data lineage maps, and interface designs to support complex integration scenarios.
• Develop and maintain detailed source-to-target mapping documents, clearly specifying data transformations, logic rules, and mappings between data sources and destination systems.

Modern Data Stack Expertise:

• Champion effective usage of cloud-native technologies and platforms, including data ingestion (Fivetran, Airflow), data transformation (dbt), containerized deployments (Docker, Kubernetes), and advanced visualization tools (PowerBI, Tableau).
• Promote rigorous adherence to enterprise-wide data governance frameworks, data cataloging tools, metadata management, and regulatory compliance (e.g., GDPR, CCPA).

Technical Stakeholder Communication:

• Serve as a critical liaison, articulating complex technical strategies to diverse stakeholders including business leadership, data engineering teams, and end users.
• Facilitate rigorous user acceptance testing (UAT) and technical validation processes, ensuring product releases meet precise business and technical quality standards.

Change Management and Technical Collaboration:

• Drive technical change initiatives by effectively communicating architecture updates, process improvements, and technical standards across cross-functional teams.
• Support the successful operationalization and continuous improvement of data solutions through agile sprints, retrospectives, and iterative product enhancements.

Qualifications and Requirements

• Essential: BA/BS degree in Operations Research, Computer Science, Statistics, Data Science, Industrial Engineering, B2B experience preferred, Information Management, or related quantitative discipline.
• Understanding of COGS, Rebates, etc processes on B2B customers
• Minimum 5 years of experience as a Business Analyst, with at least 2 years in technical roles specializing in customer data management or analytics.
• Deep technical knowledge of modern data stack components, including data lakes, data warehouses, and cloud analytics ecosystems.
• Extensive experience with advanced SQL, Python scripting, and robust data visualization tools (PowerBI, Tableau, Looker).

Technical Proficiency:

• Expert-level familiarity with cloud data platforms (Snowflake, Azure Synapse, Google BigQuery).
• Strong technical background in CRM and ERP integration (Salesforce APIs, SAP ECC, Oracle EBS).
• Proficiency with