Responsibilities Translate Business Requirements to Conceptual, Logical and Pysical Data Models
Recognize the need for a specific relational design – OLTP, OLAP, Data Warehouse – from a set of requirements and/or from a Logical Data Model
Participate in mapping of Logical to Physical Data Models and vice versa
Perform model creation for large set of data which are being sourced to Big Data

Role Requirements

Strong Data Modeller with Financial Services experience
Knowledge of and experience using data models and data dictionaries in a Banking and Financial Markets context

"Knowledge of one or more of the following domains (including market data vendors):

o Party/Client

o Trade

o Settlements

o Payments

o Instrument and pricing

o Market and/or Credit Risk"

Demonstrate a continual desire to implement “strategic” or “optimal” solutions and where possible, avoid workarounds or short term tactical solutions
Working with stakeholders to ensure that negative customer and business impacts are avoided
Manage stakeholder expectations and ensure that robust communication and escalation mechanisms are in place across the project portfolio
Good understanding of the control requirements surrounding data handling

Experience/Skillset

Excellent analytical skills and commercial acumen
Experience in ETL/ELT as well as Entity Relationship (ER) data modelling
Understanding of slowly moving dimensional Datawarehouse (star schema, kimball dimensional data modelling)
Good knowledge of SDLC and formal Agile processes as well as testing experience
Can write SQL (NoDQL) and Python queries, Scala knowledge preferable and navigate data bases especially Hive, CMD, Putty, Note++
Strong self-starter with strong change delivery skills who enjoys the challenge of delivering change within tight deadlines
Strong verbal and written communication skills
Ability to manage multiple priorities
Knowledge of and experience using data models and data dictionaries in a Banking and Financial Markets context
Preferable knowledge and experience in Data Quality & Governance
Understanding of on-prem and Cloud Data Lakes as well as data warehouses architecture
Enthusiastic and energetic problem solver to join an ambitious team
Business analysis skills, defining and understanding requirements
Attention to detail
Ability to communicate effectively in a multi-programme environment across a range of stakeholders
Knowledge of Hadoop of Google Big Query is a plus

Something looks off?