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:


* Bachelor's degree required (analytics, finance, 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 designing semantic models for enterprise analytics (dimensions, measures, hierarchies, ag...