MicroStrategy Engineer

PACSUN•Anaheim, CA

5d•$95,000 - $115,000

About The Position

The MicroStrategy Engineer is a hands-on technical role responsible for developing, enhancing, administering, and supporting Pacsun’s enterprise reporting and analytics solutions using Strategy (formerly MicroStrategy) on the Snowflake retail data warehouse. Reporting to the Manager, Business Analytics & Reporting, the Engineer maintains and evolves the Strategy metadata and reporting environment, builds business reports and analytics, supports upgrades and production operations, and troubleshoots issues. The role requires understanding both the technology and retail business context behind the data, and applying AI tools and capabilities to improve analytics and BI development. The Engineer partners with stakeholders across merchandising, planning, inventory, stores, eCommerce, finance, supply chain, and marketing, and collaborates with the Manager, data engineers, the Data Architect, IT teams, and external partners. The role also supports cross-functional initiatives, including ERP and financial systems transformation work related to reporting. This is a full-time position in a professional office environment using standard office equipment. Occasional evening and/or weekend work may be required during high-volume periods, and hotel, airplane, and car travel may be required.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Analytics, Engineering, or a related field, or equivalent practical experience.
At least 3 years of hands-on Strategy (formerly MicroStrategy) development and engineering experience in an enterprise environment.
Strong working knowledge of Strategy metadata and architecture, including metrics, attributes, facts, schema objects, reports and dashboards, security, and troubleshooting.
Strong SQL skills and thorough understanding of relational databases, data warehousing, dimensional modeling, and analytical data structures.
Retail industry experience and practical understanding of sales, inventory, cost, margin, and related retail analytics and reporting concepts.
Hands-on experience with Snowflake as a cloud data warehouse, including querying and integration with Strategy.
Ability to develop enterprise reports and analytics from business requirements through testing and production support.
Experience learning, adopting, and applying AI or generative AI tools in a BI or analytics context, such as natural language query, AI-generated narratives, or AI-assisted development.
Strong analytical, troubleshooting, documentation, and communication skills, including ability to work effectively with business users, technical peers, and external partners in a fast-paced production environment.

Nice To Haves

Fashion, apparel, or specialty retail experience.
Experience with Strategy administration, upgrades, performance tuning, and environment migrations.
Strategy (MicroStrategy) Developer- or Architect-level certification.
Snowflake certification, such as SnowPro.
Exposure to Tableau, Power BI, or other analytics platforms.

Responsibilities

Design, develop, test, deploy, and support Strategy enterprise reports, dashboards, dossiers, metrics, and analytical applications, from business requirements through testing and production support.
Maintain and enhance Strategy metadata, including attributes, facts, metrics, hierarchies, transformations, filters, prompts, schema objects, security, and reusable components.
Apply retail business logic for sales, inventory, cost, margin, gross margin, and sell-through, ensuring measures are calculated and presented correctly.
Use SQL, Snowflake, relational databases, and dimensional models to validate reporting logic, reconcile reports with source data, resolve discrepancies, and tune report SQL in collaboration with data engineers.
Provide production support, including root-cause analysis, defect resolution, performance tuning, monitoring, and user support.
Support Strategy upgrades, patches, migrations, environment management, regression testing, and release deployment using tools such as Workstation, Object Manager, Integrity Manager, and Command Manager.
Integrate AI features such as natural language query, AI-generated insights and narratives, and anomaly detection into dashboards; use GenAI tools to accelerate development, documentation, and testing; evaluate new tools and share effective practices with the team.
Partner with business stakeholders to clarify requirements and deliver usable, accurate solutions.
Follow data governance, row-level security, access control, and responsible AI practices, including accuracy checks on AI-generated output.
Document report logic, metadata changes, technical designs, and operational procedures, and improve reporting performance, usability, maintainability, and development standards.
Stay current on Strategy platform updates and emerging AI analytics trends.
Communicate clearly with technical and non-technical stakeholders and contribute to team learning by sharing AI and data knowledge.
Support cross-functional initiatives, including ERP and financial systems transformation work, as they relate to reporting.
Model integrity, ownership, collaboration, confidentiality, transparency, and accountability in work across IT, data engineering, and business teams.