Role Summary
We are looking for a Senior Data Analyst with 8+ years of experience to join our Finance Data Office (FDO). This role is highly data-driven and requires someone who can think like a data architect, understand complex finance datasets end-to-end, identify patterns and anomalies, and translate insights into actionable outcomes for Finance leadership. The candidate should be hands-on with modern data platforms, SQL, and BI tools, and able to work independently with business and technology stakeholders.
Key Responsibilities
Data Analysis & Insights
- Perform deep-dive analysis on finance datasets (revenue, expense, margin, accruals, rebate, allocations, close/reporting) to identify trends, patterns, anomalies, and drivers.
- Build and maintain KPI frameworks and metrics definitions (golden metrics) with consistent logic across reports.
- Conduct root-cause analysis and explain variances (MoM/QoQ), including reconciliation and tie-outs across sources.
- Produce executive-ready insights and storylines for dashboards and finance walkthroughs.
Data Mindset (Analyst + Architect)
- Understand data lineage across systems and define source-to-target mappings, data models, and transformation logic.
- Partner with data engineering to design curated datasets (semantic / consumption layer) optimized for BI and analytics.
- Drive data quality rules, controls, and monitoring: completeness, accuracy, timeliness, reconciliation checks, and exception reporting.
- Document business logic, definitions, and assumptions in a structured way (data dictionary, metric catalog).
Collaboration & Delivery
- Work directly with Finance stakeholders to gather requirements, clarify logic, and iterate quickly.
- Support release planning and adoption: UAT support, user training, and change management for dashboards.
- Ensure governance and compliance alignment (access controls, auditability of logic, documentation).
Required Skills & Experience (Must-Have)
- 8+ years in data analytics / BI / finance analytics roles (enterprise scale preferred).
- Expert in SQL (complex joins, window functions, performance tuning mindset).
- Strong understanding of data modeling concepts (dimensional modeling, facts/dimensions, star schema, semantic layer).
- Hands-on experience with Power BI or Tableau (dashboard design, measures, performance, usability).
- Strong experience working with data platforms / warehouses / lakehouse (Databricks, Snowflake, Redshift, Synapse, etc.).
- Proven ability to handle data quality + reconciliation + controls in finance reporting contexts.
- Strong communication: can explain complex data findings clearly to business leaders.
Good-to-Have (Preferred)
- Exposure to Databricks / Spark / PySpark for large-scale analysis.
- Experience with ETL/ELT tools (ADF, Airflow, dbt, Informatica, etc.).
- Experience with data governance/metadata tools and practices (catalog, lineage, metric definitions).
- Familiarity with financial close/reporting processes and regulatory reporting concepts.
- Experience building reusable semantic models and certified datasets for enterprise BI.
