Sql server business intelligence Work, Jobs (with Salaries)

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Customer Success Engineer

SafetyCulture -
Manchester

Apply Now

Job details

Permanent | Full-time

Qualifications

Go
SQL
JavaScript
Ruby
Software development
APIs
AI
Python

Full job description

We’re a global tech company, just not the kind you’re picturing. Our team of nearly a thousand people wakes up every day to make our product and our customers’ lives better. At SafetyCulture, you’ll hear “yes, let’s give it a shot” more often than “that’s not how we do things here.”

People join because we’re building tools that make work better for the 3 billion people who keep the world moving: factory floor operators, baggage handlers, truck drivers, servers, store assistants. The ones who make things happen. We’ve got the scale and innovation you’d expect from big tech. The difference? No endless layers of sign-off. No corporate theatre. Just smart, experienced people solving real problems fast.

The scale is big, but the ownership is personal. Every full-time team member gets equity: real skin in the game. When we grow, you do too. This next chapter is about scaling with intelligence, not just size, fueled by operational maturity, a clear vision, and a strong focus on AI.

Role Purpose

This Customer Success Engineer role exists to unlock technical value for SafetyCulture’s Enterprise customers, designing and implementing solutions that ensure customers integrate deeply with the platform and realise measurable operational outcomes, while bridging the gap between Go-to-Market (GTM) teams and Product, Design & Engineering (PDE).

Key Responsibilities

Own technical solution design for Enterprise customers: from scoping integrations and data workflows through to working implementations that enable full platform value.
Partner with Customer Success Managers (CSMs) to build implementation plans that accelerate time-to-value for managed accounts.
Work alongside Account Executives (AEs) during pre-sales to communicate technical platform capabilities (APIs, security architecture, and cloud integrations) and resolve technical blockers in the sales cycle.
Act as a technical bridge between GTM and PDE, capturing and routing customer integration feedback that shapes the product roadmap.
Build lightweight technical solutions (scripts, automations) that extend platform capability for specific customer use cases.
Advise customers on integration architecture: how to connect SafetyCulture to their existing systems effectively and sustainably.
Partner with the API and Integrations Engineering team to resolve complex customer requirements and advocate for platform improvements that benefit the broader customer base.

Required Skills & Experience

Technical Skills

Proven ability to design and implement data solutions: writing SQL queries, modelling relational databases, and translating raw data into business-relevant insights.
Comfortable building across scripting or programming languages (e.g. Python, JavaScript, Ruby, Golang) to automate workflows or extend platform capabilities for specific customer use cases.
Able to navigate a wide variety of enterprise system architectures, data models, and integration patterns.
Confident reading API documentation and building or troubleshooting API integrations in enterprise environments.
Background spanning software development and data analytics; comfortable moving between building solutions and communicating data-driven insights to non-technical stakeholders

Behavioural Skills

Translates fluently between technical and non-technical audiences: equally credible in an engineering deep-dive and a customer-facing session with business stakeholders.
Stays organised across a high-volume, concurrent workload; switches context quickly without losing quality or missing detail.
Customer-first problem solver: listens to understand the real need before proposing a solution, and brings options rather than just problems.
Self-directed and comfortable with ambiguity; identifies what needs to be built or fixed without waiting for a detailed brief.
Team-first mindset: invests in the success of CSMs, AEs, and engineering partners, not just their own outcomes

AI Skills

Uses AI tools to accelerate integration work, drafting technical specs and documentation, analysing customer data to surface insights, and building automations faster.
Applies AI coding assistants fluently in day-to-day work; evaluates AI-generated code for quality, correctness, and security before deploying.
Proficient with AI tools: independently identifies where AI adds leverage in their workflows and adopts new capabilities without direction.

Success Looks Like

Operating independently across the full customer engagement lifecycle: scoping, designing, and delivering technical solutions without needing close direction.
Consistently high customer confidence scores in post-engagement surveys, reflecting the quality and clarity of technical guidance delivered.
Enterprise customers are integrating successfully and realising value from the platform faster, evidenced by reduced implementation cycle times and lower escalation rates.

Key Stakeholders

Customer Success Managers: primary internal partners on ongoing customer planning and value delivery.
Customer Onboarding Managers: primary internal partners on initial customer implementation planning and value delivery
Account Executives: Sales partners during pre-sales technical evaluation and solution scoping.
API and Integrations Engineering team: engineering counterparts for complex customer requirements and product feedback.
Technical Architects: Pre-sales counterparts that will scope and architect large, complex customer solutions and hand off to CSEs to implement.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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