Data Analyst Position

We require an articulate, self-starting Data Analyst with experience working with financial services systems and data flows (Front Office, Middle Office, Surveillance & Compliance). Candidates should have 7+ years of experience and have previously held similar, mid-level positions in FS industry organisations, although we will consider candidates with an exceptional experience from other industries. (fintech, telco etc.)

Key Skills & Technology

Candidates should be able to demonstrate competencies in the following areas:

Data Gathering
Data Modelling
Data Querying
Data Mapping
Data Cleansing & Preparation
Data Migration
Data Visualisation & Analytics

Experience should include the use of technology platforms that support the above data-centric skillsets – examples include:

Google Analytics
Erwin, Lucid, DbSchema
MySQL, Snowflake, Redshift
Informatica, Talent
Informatica, Google Refine
Azure Data Migration
PowerBI, Qlik, Tableau

And a high degree of competency in the use and manipulation of Excel Spreadsheets in support of data-wrangling activities.

Soft Skills:

Research Skills: Ability to navigate complex datasets, using proven frameworks and processes
Self-Starter: Ability to work dynamically with key stakeholders, and demonstrate progress against a plan
Articulate: Ability to clearly communicate with stakeholders as part of the discovery activities, and steering in terms of progress reporting
Strong written communication skills: Ability to create artefacts that reflect finds and proposals
Collaboration: Work as part of a wider team and play a can-do attitude

Domain Expertise:

Financial Services – Front Office, Middle Office, Surveillance

Responsibilities:

Data Discovery
Creating Artefacts pertaining to data discovery – Architecture, Models. Current State Document
Creating Artefacts pertaining to data solution – option Paper, Solution Arch, Future State Document
API Development (Requirements Gathering)
Data manipulation using SQL, Python, R, Excel spreadsheets,
Planning and execution of data-related activities