We are looking for an experienced Technical Data Modeller to join our Finance Data Platform team and lead the design and implementation of robust, scalable finance data models on Databricks. Youll play a pivotal role ensuring data integrity, consistency, and usability for analytical and operational use cases such as reporting, BI (Power BI), and advanced analytics.

You will work closely with data engineers, architects, and finance stakeholders to translate business requirements into high-quality data models that support the enterprise data strategy.

Key Responsibilities :

- Develop conceptual, logical, and physical data models tailored to finance data domains.

- Collaborate with data engineering teams to implement and operationalize models within Databricks.

- Define, standardize, and maintain data models, data dictionaries, and metadata in alignment with financial business semantics.

- Optimize data structures for performance, scalability, and downstream analytical consumption (Power BI, analytics workspaces).

- Lead data quality design, validation processes, and ensure governance best practices are embedded in model design.

- Support integration with data pipelines, ETL/ELT workflows, and documentation of data flows.

- Act as a technical guide and mentor for junior modellers where applicable.

Required Skills & Experience :

- Proven experience in data modelling (conceptual, logical, and physical) within large-scale data environments, ideally in finance or enterprise contexts.

- Hands-on experience implementing data models on Databricks.

- Strong proficiency with SQL, data warehousing, and dimensional modelling (e.g., star/snowflake schemas).

- Solid understanding of finance data structures, accounting principles, and related business semantics.

- Familiarity with data governance, master data, and metadata management practices.

- Excellent collaboration skills to partner with engineers, architects, and finance business teams.

- Detail-oriented with a strong focus on data integrity, performance, and usability.

Nice-to-Have :

- Experience with modelling tools like ERwin / ER Studio, SQLDBM, or similar.

- Exposure to finance data reporting systems (e.g., Power BI, Looker, Tableau).

- Knowledge of cloud data architectures and data lakes.