Enterprise Sales Engineer

Description

The company is Rimes, which provides an intelligence fabric for capital markets. It combines a trusted data network with intelligence architecture to turn fragmented data, operations and workflows into intelligence that supports decisions. Its clients include large institutional investors, asset managers and service providers, and the firm says they rely on it for investment decisions covering more than US$ 75 trillion in AUM each year.

This is a senior pre-sales and solution design role that reports to the Head of Enterprise Solutions. You will work alongside Enterprise Sales and Account Management to explain and demonstrate the value of the company's investment data managed services and investment intelligence platform. You will own the technical side of sales for complex enterprise deals across EMEA, from early discovery through solution design, demos, proof-of-value and handover to delivery.

You will advise CIOs, COOs, and heads of investment data and technology, risk, performance and operations as a trusted technical adviser.

Responsibilities

• Run technical and functional discovery sessions with prospective clients alongside sales and account management, covering data, governance, technology and operating model issues across the investment lifecycle. Dig past stated requirements to find structural weaknesses in data, governance and operations.
• Design end-to-end solutions covering enterprise data management, portfolio oversight, rebalancing, data quality, operational resilience and regulatory obligations.
• Design and explain enterprise investment data architectures built on the company's capabilities in multi-asset data management; benchmarks, indices, reference data, pricing, ESG and research; performance, risk, attribution and regulatory reporting; and data platform integration, including lakehouse designs on Databricks or Delta Lake and cloud warehouses such as Snowflake or Azure Synapse.
• Turn complex challenges, such as private markets data, custodian transitions, operating model change, regulatory compliance and the choice between internal and outsourced models, into a coherent architecture.
• Own the technical pre-sales work for the company's managed data services (benchmarks, indices, reference data, pricing, research, ESG and corporate actions) and its investment intelligence platform, which covers Total Portfolio View, rebalancing under Strategic Asset Allocation and the move to Total Portfolio Approach.
• Build demonstrations around each client's real operating model rather than generic feature tours. Lead high-stakes proofs of concept that balance depth, speed and commercial impact, and frame results in measurable business outcomes.
• Work with sales and account management to position the company against incumbent vendors and internal build options. Own the technical story in RFPs, RFIs and executive presentations, shaping how evaluation criteria are set as well as answering them.
• Turn detailed client requirements into Statements of Work and help scope implementation and managed services accurately.
• Hand pre-sales work to Professional Services and implementation teams with clear context on solution intent, client priorities and success criteria.
• Work across sales, marketing, product, engineering and delivery. Share knowledge, build solution materials and best-practice frameworks for internal enablement.
• Relay client needs to product and engineering by qualifying enhancement requests, and feed market intelligence back to shape go-to-market strategy.

Requirements

• Required: strong experience in financial services, investment management or capital markets.
• Solid understanding of investment data and its workflows, including pricing, benchmarks, corporate actions, reference data and analytics.
• Proven background in pre-sales, solutions engineering or consulting within enterprise technology or data platforms.
• Ability to explain complex technical ideas clearly to both technical teams and executives.
• Experience with the particular challenges of EMEA clients, including asset managers and asset owners.
• Familiarity with modern data platforms such as Databricks, Snowflake or cloud-native warehouses, and the ability to show how the company's data delivery fits into a client's existing lakehouse and cloud setup.
• A consultative, outcome-focused approach to clients.
• Strong written and verbal communication, including executive presentations.
• Able to work independently and also thrive in a collaborative, high-performance team.
• Commercial judgement for scoping solutions and supporting deal strategy.
• Able to use AI tools effectively to work more efficiently.

Conditions

Only selected candidates will be contacted for interviews.

The company is committed to diversity and inclusion across recruitment, retention, progression and training.

Benefits

• Work with some of the largest and most sophisticated asset owners and managers.
• Help shape the future of investment data management and operational resilience.
• Influence product direction, solution design and client success at enterprise scale.