Transformation and Innovation Team Analytics Solutions Senior Associate

Join a team that delivers innovative products and solutions that enable advanced use of data and technology to drive process optimization and enhanced analytics for Finance P&A and Business Management.

As a Analytics Solutions Senior Associate within the you will build AI-ready analytics datasets and semantic models with a strong emphasis on Databricks lakehouse engineering as the foundation for Finance reporting and planning use cases and support a strategic migration from Oracle Database / Essbase to a modern stack using Databricks for curated governed data products and Atoti for semantic/cube analytics.

Job Responsibilities:

• Design and deliver curated analytics datasets in Databricks (conformed dimensions metric-ready fact tables standardized grains) that serve as the authoritative foundation for Finance semantic models and downstream consumption.
• Develop and optimize transformation logic and pipelines in Databricks (e.g. incremental processing patterns performance tuning cost-conscious compute usage) partnering with Technology while owning the data/modeling requirements and validation.
• Translate Databricks curated datasets into Atoti semantic/cube models (dimensions hierarchies measures aggregation logic) and ensure performance and usability for Finance personas.
• Create and maintain structured semantic metadata (business definitions synonyms calculation narratives grain constraints permitted aggregations known limitations) to improve GenAI grounding and reduce ambiguity/hallucination risk in natural-language analytics.
• Convert Essbase/Oracle logic into lakehouse and semantic-layer constructs documenting mapping rules assumptions and gaps; support parallel runs and model validation.
• Ensure curated data semantic models support Excel workflows via AnaplanXL including drill paths hierarchies measure behavior and user-facing definitions and contribute to cutover readiness issue triage adoption metrics and decommissioning of legacy Essbase/Oracle-dependent reporting by ensuring Databricks datasets and semantic models meet functional and performance requirements.
• Establish reusable Databricks patterns (data quality checks validation harnesses reconciliation templates) and contribute to playbooks for Finance lakehouse and semantic modeling.

Required qualifications capabilities and skills:

• Bachelors degree required (analyticsfinance engineering or related field) or equivalent experience; 4 years of experience in data modeling analytics engineering data platform transformation or Finance analytics roles (financial services preferred).
• Hands-on experience building curated datasets using Databricks (or equivalent lakehouse platform) including strong SQL and data transformation skills and an understanding of performance/cost tradeoffs..
• Experience designingsemantic modelsfor enterprise analytics (dimensions measures hierarchies aggregation behavior) and partnering with BI/consumption teams.
• Working knowledge ofGenAI integration patternsfor analytics (e.g. natural-language-to-metrics grounded responses via semantic layers) and how metadata quality impacts outcomes.
• Ability to translate legacy logic (e.g. Essbase/Oracle) into modern curated-layer and semantic-layer implementations including reconciliation and validation.
• Strong analyticalindependentproblem-solving and communication skills; able to partner effectively across Product Technology and Finance stakeholders.
• High attention to detail ownership mindset and ability to manage multiple priorities in a fast-paced environment.

Preferred qualifications capabilities & skills:

• Experience with Atoti (or similar OLAP/semantic tooling) and understanding of cube design/performance considerations.
• Familiarity with Excel-based consumption patterns and add-ins (including AnaplanXL).
• Hands-on familiarity withModel Context Protocol (MCP)concepts and patterns (tool/schema exposure semantic discovery guardrails) especially in the context of analytics/semantic layers.
• Exposure to data quality rules lineage documentation access controls/entitlements and audit/control expectations in Finance and agile delivery experience and familiarity with Jira/Confluence.