Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Salesforce Engineer

London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior/Lead Data Engineer

Director, Data Engineering

Director, Data Engineering

Director, Data Engineering

Director, Data Engineering

Director, Data Engineering

Role: Lead Salesforce Engineer

Salary: Up to £100,000 per annum

Work Model: Hybrid (London)

Mason Frank is proud to be partnering with a prominent company in financial services sector to find a Lead Salesforce Engineer. The company is undergoing a transformative journey, expanding its global footprint and enhancing the value it delivers to clients.

Key Responsibilities:

Lead the design and development of Salesforce solutions, including Sales Cloud, CPQ, and Marketing Cloud.
Manage and mentor a team of Salesforce administrators, guiding them through complex technical challenges.
Build and maintain strong relationships with internal teams (Sales, Marketing, Technology) and external partners to deliver successful projects.
Drive Salesforce security best practices and ensure data compliance across all platforms.
Collaborate on the creation of a robust Salesforce architecture that integrates seamlessly with other business platforms.
Oversee the implementation of automation processes to improve the efficiency of internal teams, including sales and marketing.
Manage Salesforce user administration tasks, including system security, role modifications, and process optimization.
Develop and deliver Salesforce dashboards and reports to support business decisions and performance tracking.
Ensure a smooth deployment pipeline between Salesforce environments.What We're Looking For:

Proven leadership experience within a Salesforce environment, with the ability to mentor and guide teams.
Extensive hands-on experience with Salesforce technologies: Sales Cloud and Marketing Cloud.
Strong problem-solving skills with a focus on delivering efficient, scalable solutions.
Excellent communication and collaboration abilities, capable of working with cross-functional teams and external partners.
In-depth knowledge of Salesforce security and data modelling.
Experience with large-scale Salesforce deployments, from design to delivery.
Ability to translate business requirements into technical Salesforce solutions.Desirable:

Experience working with Salesforce consultancies or integrating Salesforce with financial systems.
Proficiency in Apex programming and Salesforce certifications (Sales Cloud, CPQ, Marketing Cloud).
Experience with SQL, SOQL, and Marketing Cloud integration options.Application Process: If this sounds like the role for you, and you're excited to work at the cutting edge of Salesforce technology, we'd love to hear from you. Please click the link or send your CV to (url removed)

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.