About the Role
We're seeking a Senior Data Analyst to partner with our Data Team, bridging business strategy and technical execution. You'll turn complex business needs into scalable, data-driven solutions, uncover key insights, and identify high-impact data use cases. This role supports our data modernization roadmap, enabling unified reporting, trusted master data, and scalable analytics across global business units.
Key Responsibilities
- Analysis & Insights: Analyze enterprise data to find trends and actionable opportunities that inform strategy.
- Use Cases & Requirements: Work with stakeholders to define data use cases and translate business needs into technical specifications and analytical models.
- Gap & Impact Assessment: Compare current-state and future-state data and infrastructure; identify gaps and mitigation strategies.
- Data Quality & Profiling: Assess completeness, consistency, and accuracy of structured and semi-structured data; work with SMEs on source gaps.
- Integration & Engineering: Design and validate data pipelines and transformations, document lineage, and engineer features using Python and SQL.
- AI-Assisted Analytics: Use LLM and AI tools (e.g., generative AI, prompt-based exploration) to speed up analysis and documentation.
- Reporting & Visualization: Build and maintain dashboards and reports that communicate findings clearly.
- Governance & Documentation: Maintain the business glossary, data dictionary, and metadata in line with governance standards.
- Testing & Validation: Validate new or transformed datasets for integrity and business alignment.
- Collaboration: Partner with data engineers, product managers, and business SMEs.
Required Qualifications
- 8–12 years in data analytics, business analysis, or data management
- Advanced SQL, including optimizing large, complex datasets
- Python proficiency (Pandas, NumPy) for analysis and feature engineering
- Experience building dashboards with AI-enabled or similar visualization
- Strong knowledge of data architecture, governance, MDM, and lineage
- Proven ability to scope data use cases and turn insights into recommend
- Strong analytical, stakeholder management, and communication skills
- Basic familiarity with AI/ML concepts and AI-assisted tools (no deep mo
Preferred
- Snowflake, Databricks, or Hadoop/Spark experience
- Data catalog/governance tools (Collibra, Alation)
- Familiarity with D&B data hierarchy, enrichment, or similar reference data systems
Tech Stack
SQL (PostgreSQL, Snowflake, Redshift) · Python (Pandas, NumPy) · AI visuacket · JIRA/Confluence
