BSA-DataOps

Core Strengths - Communication & Collaboration

• Exceptional written and verbal communication skills, with the ability to clearly explain systems, data flows, analytical concepts, and impacts to non-technical stakeholders.
• Proven ability to build trust and credibility with business partners, guiding discussions that clarify needs, priorities, and success criteria.
• Skilled in creating clear documentation, diagrams, and presentations that align business goals with technical solutions.
• Comfortable facilitating conversations across diverse audiences, from executives to business users to technical teams.
• Self-directed and execution-oriented, with the ability to independently drive solutions forward while managing multiple, competing priorities.

Experience & Technical Foundation (Used To Enable Communication)

• 7+ years of experience as a Systems Analyst supporting Data Analytics, Data Warehousing, or Data Science initiatives.
• Strong SQL expertise (7+ years), enabling thoughtful analysis, validation of requirements, and collaboration with data engineers and analysts.
• 3+ years of experience designing Data Marts, with a solid understanding of dimensional modeling concepts (facts, dimensions, star/snowflake schemas).
• 3+ years of experience with Power BI, including partnering with business users to design dashboards that tell clear, meaningful stories.
• Experience leading or supporting the implementation of new data platforms or improving existing platforms in close collaboration with technical teams.

Business Partnership & Data Platform Enablement

• Demonstrated ability to translate business and operational needs into data platform capabilities, process improvements, and analytics solutions.
• Experience working closely with data platform engineers, solution delivery teams, IT, and business stakeholders to evaluate, select, implement, and optimize modern data platforms.
• Comfortable acting as a liaison between technical and non-technical teams, ensuring alignment, shared understanding, and successful adoption.

DataOps & Modern Data Platform Exposure

• Functional or hands-on experience supporting DataOps practices, including:
  • Data engineering concepts (ETL/ELT, real-time streaming, virtualization)
  • Data catalogs, lineage, and metadata management
  • Data quality monitoring and observability
  • Platform performance, scalability, reliability, and cost awareness
• Ability to identify gaps in data workflows and analytics lifecycles, and work collaboratively to improve end-to-end data delivery.
• Clear understanding of how governance, automation, and observability support trusted, enterprise-ready analytics and AI solutions.