Manager, Data Ops, Platforms And Analytics Operations
Listed on 2025-10-27
-
IT/Tech
Data Analyst, Data Science Manager, Business Systems/ Tech Analyst, Data Engineer
Manager, Data Ops, Platforms And Analytics
Build a scalable, governed BI ecosystem to deliver trusted executive dashboards and reports
Location: Carlsbad, California, United States
Compensation: $135, USD / year
Job Tags: Operations
AboutThe Role
Manager, Data Ops, Platforms, and Analytics
FASHIONPHILE is revolutionizing the ultra-luxury fashion experience to create a sustainable alternative that extends the life cycle of products and makes them more accessible to a diverse customer base. As we strive to become the world s most sought-after brand in luxury re-commerce, we know it s our team members who make it all happen! We value diversity in our people, perspectives, and products.
For us, it s the only way to cultivate the creativity and innovation essential to achieving our mission and supporting our customers. We do this both in-person and through our digital omni-channel experiences. If you re someone who embraces change, is authentic, and wants to make an impact this is the place for you.
We are looking for a full-time Manager, Data Ops, Platforms, and Analytics to join our Data Science and Analytics team in our Carlsbad, CA location! The Manager, Data Ops, Platforms and Analytics is a technical leader who builds and optimizes BI solutions using data sources to deliver high-quality executive and functional dashboards, robust KPI definitions, and governed reporting. This role oversees day-to-day data operations, manages team projects, and mentors team members to build a strong, capable data function.
Responsibilities Include:- Design, build, and optimize BI solutions using data in Enterprise Data Warehouse and multiple data sources stored in AWS (Redshift, S3), and data from other applications, to deliver executive and functional dashboards, robust KPI definitions, and governed reporting.
- Integrate, configure, and roll out new BI and reporting tools; oversee and coordinate data integration efforts—ensuring that integrated data sources are available, accessible, high-quality, and fit-for-purpose for reporting/analytics; partner closely with Data Engineering, articulate business requirements, validate data integration projects, and own outcomes like unified reporting, governance, and data quality for analytics (not the hands-on technical builds).
- Oversee day-to-day BI, reporting, and analytics operations, including managing project intake, assignments, ad hoc requests, incident management with appropriate urgency, and ongoing team delivery cycles. Collaborate with stakeholders to define requirements, deliver actionable insights, provide training, and maintain clear process documentation to ensure business needs are met.
- Maintain and continually improve a governed BI ecosystem, including semantic layers, KPI glossary, and robust monitoring of data lineage and quality, to drive trusted, impactful business insights and reporting.
- A master s degree in data science, analytics, engineering, computer science, mathematics, business analytics or related discipline.
- 4+ years of hands-on experience specifically managing BI, reporting, and operational analytics teams—including direct responsibility for delivering executive and functional dashboards, integrating and validating data from cloud data warehouses (e.g., Redshift), S3, and multiple business systems, maintaining data quality and governance, overseeing incident management and SLA compliance, enabling self-serve reporting, and leading successful tool integration and process improvement projects.
- Certifications - Tableau, PMI, Scrum Master, AWS.
- Data Strategy & Architecture:
Experience building scalable BI/reporting ecosystems (Tableau, Looker, Sisense/Periscope, PBI, or similar). - Tool & Tech Expertise:
Hands-on experience with additional BI, reporting, data integration (Redshift, AWS, S3, cloud and enterprise platforms), or cloud tools. - Statistical and ML Methods:
Advanced knowledge of statistical and machine learning methods including hypothesis testing, regression, classification and clustering. - Leadership and Team Skills:
Highly motivated self-starter, strong leadership skills, and proven ability to build, mentor,…
(If this job is in fact in your jurisdiction, then you may be using a Proxy or VPN to access this site, and to progress further, you should change your connectivity to another mobile device or PC).