Senior Data Analyst

Description

• Engage with stakeholders to understand business processes, pain points, and analytical needs.
• Map existing systems and their data models to identify integration points and gaps.
• Works to achieve day-to-day objectives with significant impact on operational results within area of work.
• May manage projects at this level, requiring responsibility for the delegation of work and the review of others' work product.
• Champion data quality, security, and governance best practices.
• Balance strategic initiatives with operational enhancements to maximize business value.
• Break down epics into actionable user stories with clear acceptance criteria.
• May be responsible for entire projects or processes within area
• Typically, responsible for coaching and reviewing the work of lower-level professionals.
• Act as the product owner for assigned data domains, ensuring data quality, accessibility, and usability.
• Define analytical and operational metrics aligned with business objectives.
• Translate business requirements into technical specifications for a modern analytical data platform.
• Collaborate with data engineering teams to design and optimize data pipelines, semantic models, and governance frameworks.
• Act as a liaison between business stakeholders, data engineers, QA analysts, and analytics teams.
• Own and prioritize the product backlog for the data platform team.
• Ensure alignment with enterprise architecture, scalability, and compliance standards
• Mentor junior analysts and foster a culture of continuous improvement.
• Provide third-level On-Call support for critical issues, including after-hours and weekends.
• Establish standards for metadata, lineage, and data stewardship.
• Facilitate workshops and discovery sessions to refine requirements.
• Produce source to target mapping documentation to support the defined metrics.
• May be responsible for providing guidance, coaching and training to other employees within functional area.
• Troubleshoot production issues and ensure timely resolution or escalation

Requirements

• Preferred Qualifications: Experience with Power BI or similar BI tools, Knowledge of DataOps practices and cloud-native architectures, Familiarity with Python for prototyping, Familiarity with data governance frameworks.
• Requires broad knowledge of area typically obtained through advanced education combined with experience. May have practical knowledge of program or project management.
• Strong understanding of the product life cycle, from discovery to delivery
• Minimum high school diploma or equivalent (GED) required.
• Typically requires a university degree or equivalent experience and minimum 4-6 years of prior relevant experience.
• Strong knowledge of enterprise systems, conceptual/logical data modeling, and integration patterns.
• 7+ years of experience in data analytics, data engineering, or product ownership roles.
• Experience with modern data platforms (e.g., Microsoft Fabric, Azure Synapse, Snowflake).
• Excellent communication and stakeholder management skills.
• Proficiency in SQL.
• May require travel
• Expertise in backlog management tools (e.g., Azure DevOps, Jira) and Agile methodologies.

Benefits

Training + Development

Interview process

Visa Sponsorship

Security clearance