Software Systems Engineer

Datatech Analytics
Published
July 1, 2022
Location
Buckinghamshire, United Kingdom
Job Type
Job Ref
J12259

Description

Senior Systems Engineer Retail Banking Up to £90000 plus 25% bonus and benefits
Location Hybrid/Marlow

Are you a problem solver, explorer, and knowledge seeker - always asking, What if? Come join us…
Our client a leader in analytics who inspire customers around the world to transform data into intelligence.

What you'll do

We are looking for a talented individual to join our Customer Advisory team within the Banking Business Unit. To help customers apply data and analytics in innovative ways so they can meet customers' needs as well as gain competitive advantage. With disciplines across data engineering, analytics, decision science and cloud computing.

Key Responsibilities
• Be a strong partner networker understanding customers, their business and the industry trends that affect them, be their trusted advisor for all things analytics.
• Comfortably and confidently position (and demonstrate) technology and its solutions to customers and prospects; scope and lead POC and POV activities.
• Support account executives with account planning, opportunity qualification, workshops, solution design and positioning, crafting proposals and bid responses and taking ownership of technical elements.
• Be an analytical or technology SME - develop thought leadership that helps build their brand.
What we're looking for
• Experience in leading / supporting technology solution design which results in new software, SaaS or cloud revenue.
• A curious mind with good probing and questioning skills to uncover customer challenges and understand business processes. The ability to articulate where and how technology solutions can address these.
• Strong communication and presentation skills coupled with analytical and problem-solving abilities and comfortable working at "C" level.
• Good understanding and experience of the retail banking sector and an understanding of the analytical process and techniques ideally with SAS, SQL or analytics open source software (R, python, Spark).

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