Engineering Team Lead (Hands-on Development)

Location: Cardiff

Hybrid/Flexible Working

Salary: Up to £75k depending on experience, plus a potential bonus up to £15k

The Role

Are you a senior engineer looking for your next step? Do you want to stay hands-on while you start building your leadership skills?

AI is changing the way we build software. Our teams are smaller, our output is higher and the pace is faster. We're looking for developers who are ready for that next step. You'll spend around 90% of your time on hands-on development. The rest of your time goes on leading a team of 4 engineers, driving delivery, and working with customers and stakeholders to get real results.

You'll join the Engineering Team at LDMS, reporting to Engineering Management and building financial software for our partners and clients.

Key Responsibilities:

These may change with the needs of the business, but the main areas are:

Technical Leadership and Development:

• Stay hands-on, writing, reviewing and shipping production code alongside your team
• Set clear technical direction for your team, keeping decisions aligned to team and product goals
• Guide design and technical decisions and support a review culture that raises quality and teaches, rather than just approves
• Spot technical debt early and work closely with your senior engineers to make sure engineering standards are adopted across the team

Delivery and Execution:

• Plan and track delivery for your team, raising risks and scope changes early
• Break complex work into deliverable increments with clear dependencies and acceptance criteria
• Run delivery sessions and workshops, such as whiteboarding an area, to shape and unblock work
• Keep an eye on dependencies with other teams, and flag them early
• Make sensible trade-offs on scope, quality and pace under pressure, and keep delivery moving
• Balance the team's time between product features and technical debt
• Keep the team's ways of working lean and adaptable, using process and meetings where they genuinely help rather than running them by default

People and Development:

• Mentor and coach your engineers through guidance, review and honest career conversations
• Run regular, structured one-to-ones focused on growth, wellbeing and clearing blockers
• Give direct, evidence-based feedback and support each person's development and progression
• Interview and hire strong engineers into your team
• Build a strong team culture with high standards and psychological safety

AI and Innovation:

• Encourage the team to use AI where it clearly helps them work faster or produce better software, and to be honest about where it doesn't
• Make sensible use of AI and automation part of how the team works day to day, rather than something tried once and dropped
• Use simple measures of how the team is doing to spot progress and catch work that's slipping or running over

Stakeholder and Communication:

• Communicate your team's technical decisions and trade-offs clearly to product and non-technical colleagues
• Manage stakeholder expectations proactively, so status updates contain no surprises
• Escalate issues to Engineering Management at the right time and in the right way, with options rather than problems
• Communicate release content to customers and support their delivery questions, giving confidence in what's coming and when

Requirements

Essential:

• A strong understanding of how good software gets built (preferably hands-on in Java/Spring Boot), with the technical judgement to guide design decisions, PR reviews and assess quality across your team
• A proven track record of planning, tracking and delivering software projects, including managing dependencies and trade-offs
• Experience managing stakeholders and communicating delivery status, risks and trade-offs clearly to non-technical and customer-facing audiences, in writing and in person
• Line management experience, or a strong track record of coaching and mentoring with the readiness to take on formal line management
• A genuine interest in progressing engineers' careers
• Comfortable using data and metrics to report progress and identify problems early

Desirable:

• An interest in using AI to help teams build software
• Experience within the financial sector
• Experience in front end development (preferably in React/TypeScript)
• Experience working with modern Continuous Integration tooling, such as Jenkins
• Experience debugging and troubleshooting issues using monitoring and observability tooling, such as Grafana, Prometheus or equivalent

The Company

LDMS are pioneers of credit software, with a 20 year history of delivering state-of-the-art loan management solutions across EMEA. Our platform has powered the formidable growth of LC Financial Holdings, now managing over €65bn in assets across 10 countries and over 7 million customer accounts.

LDMS supports multi-jurisdictional language and currency. Our processes and products ensure maximum flexibility and empower every single user to be more effective, with surety of regulatory compliance. The best technology provides a true business advantage. Based in our Cardiff tech hub, we have an 80-strong team of highly experienced engineers providing full professional services implementation support by dedicated experts.

ROLE DESCRIPTION

DATE: April 2026

JOB TITLE: Data Analyst Engineer

At Eakin Healthcare, we put patients at the heart of everything we do. We are a family-owned global medical device company with a proud heritage of innovation and care. We deliver innovative solutions across Ostomy, Respiratory, and Surgical therapies, along with our Respond home delivery service. Founded over 50 years ago, we now have a team of over 700 dedicated people across three UK manufacturing sites, 12 international sales and distribution centres and export to over 60 countries. We’ve been recognised as a Great Place to Work®! And we’re proud to be named among the Best Workplaces in Healthcare and Best Workplaces for Women.

At Eakin Healthcare, we’re united by one mission: leading with care just like we’ve been doing for over five decades.

We’re good at what we do – come and join us!

ABOUT THE ROLE

The Data Analyst Engineer will report to Eakin’s Head of Environmental, Social & Governance (ESG) and be positioned within the Compliance, Finance & Procurement Department. The Data Analyst Engineer will support the development and delivery of trusted sustainability data products which enable the business in achieving our climate objectives. As the Data Engineer Analyst will primarily be a data professional, the successful candidate will work in close partnership with the Data Team through an agreed supply and trust relationship. In addition to delivering sustainability data products, the Data Analyst Engineer will also be asked to dedicate a portion of their time to engage with other stakeholders within the Compliance, Finance & Procurement Department.

The role acts as the bridge between domain data requirements and technical data delivery, working collaboratively with the Data Team across DevOps ways of working, sprint planning, backlog refinement, solution design and development activity. This includes contributing to the design, build and maintenance of robust data structures, analytical datasets, semantic and dimensional models, and reporting solutions developed within Snowflake and associated analytics platforms.

KEY RESPONSIBILITIES

Data Modelling & Analytics Engineering

• Design, build and maintain robust analytical data models, including fact and dimension tables, that underpin trusted reporting and analytics.
• Develop, optimise and maintain data pipelines, transformations and queries to ensure reliable, performant and scalable analytical datasets.
• Own data quality across analytical layers, ensuring consistency, integrity, traceability and clear documentation.
• Support the integration of data from operational source systems into analytical environments, enabling end‑to‑end data flows from source to insight.

Reporting & Business Intelligence

• Develop and maintain Power BI dashboards and reports that deliver clear, actionable insight aligned to business priorities.
• Translate business questions and requirements into well‑defined analytical metrics, measures and visualisations.
• Ensure reporting solutions adhere to best practice in usability, performance, security and data governance.
• Support stakeholders in interpreting insights, identifying trends, risks and opportunities, and using data to inform decisions.

Analytical Tools & Applications

• Design, build and maintain lightweight analytical applications and tools (e.g. Streamlit apps) that extend insight beyond standard reporting.
• Develop interactive analytical workflows that enable deeper data exploration and scenario analysis.
• Support the deployment, operation and ongoing maintenance of analytical applications, including integration with existing platforms and reverse‑ETL processes.

Stakeholder Collaboration & Enablement

• Partner closely with business stakeholders to understand analytical needs and translate them into scalable, effective data solutions.
• Act as a bridge between technical data teams and business users across both project delivery and business‑as‑usual (BAU) activity.
• Enable confident use of data products by providing guidance, support and knowledge‑sharing on reports, dashboards and analytical tools.

Continuous Improvement

• Proactively identify opportunities to improve data models, reporting performance and analytical workflows.
• Apply and promote best practice in analytics engineering, data modelling and reporting standards.
• Contribute to the ongoing evolution of the organisation’s data platform, analytics capability and overall data maturity.

Other

• To adhere to the company’s Equal Opportunities policy and Dignity at work policy in all activities and to actively promote equality of opportunity wherever possible.
• To be responsible for your own health and safety and that of your colleagues, in accordance with the company’s’ Health and Safety policy.
• To adhere to the company’s Quality policy and Environmental policy.
• To undertake other duties as may be reasonably required.
• Willingness to occasionally travel between Eakin’s manufacturing locations in Northern Ireland & Wales.

WHAT WE’RE LOOKING FOR

Essential

• Proven experience in an analytics engineering, data analyst or similar role, operating at the intersection of data engineering and analytics.
• Demonstrable experience designing and maintaining analytical data models, including fact and dimension tables, to support reporting and insight.
• Hands‑on experience developing and optimising data pipelines, transformations and queries to produce reliable, performant analytical datasets.
• Strong experience delivering business intelligence and reporting solutions, including Power BI dashboards and reports, for non‑technical users.
• Strong SQL capability and experience working across modern analytical data environments.
• Practical experience applying best practice in data modelling, data quality management and documentation.
• Experience translating business questions into analytical metrics, measures and visualisations.
• Experience supporting business‑as‑usual (BAU) reporting and analytics workloads in a production environment.
• Proven ability to work closely with business stakeholders to understand analytical requirements and translate them into effective data solutions.
• Ability to communicate complex data concepts clearly and confidently to non‑technical audiences.
• Experience supporting users to interpret insights and use data products effectively in decision‑making.
• Strong analytical and problem‑solving skills, with attention to detail and a focus on data integrity.
• Ability to manage competing priorities across project work and BAU activity.
• A collaborative, proactive approach with a continuous‑improvement mindset.

• A passion for tackling sustainability challenges such as climate change, waste and modern slavery.
• A willingness to complete a formal qualification in carbon accounting (5xdays).

Desirable

• Proficiency in building lightweight analytical applications (e.g. Streamlit or similar tools).
• Ability to develop interactive analytical workflows beyond standard dashboard reporting.
• Knowledge of reverse‑ETL and operational analytics use cases.
• Familiarity with cloud‑based data platforms and modern analytics stacks.
• Understanding of data governance, semantic modelling and enterprise reporting standards.
• Capability to integrate data from multiple operational systems into analytical environments.
• Comfortable operating within complex, matrix or multi‑stakeholder organisations.
• Exposure to regulated or data‑intensive sectors (e.g. manufacturing, healthcare).
• Contribution to the development and maturity of data and analytics capabilities.
• Degree (or equivalent) in a quantitative discipline (e.g. data, engineering, science, mathematics, economics).
• Demonstrated commitment to continuous professional development in data/analytics.
• Exposure to sustainability, ESG or regulatory reporting data (e.g. carbon accounting or supplier engagement).

KEY WORKING RELATIONSHIPS

Internal

• Primarily data professionals & Head of Environmental, Social & Governance, with collaboration within other teams such as, Compliance, Finance & Procurement.

External

• IT Supplier

ADDITIONAL INFORMATION

• None

COMPETENCIES

Customer Focus

Building strong customer relationships and delivering customer-centric solutions.

Tech Savvy

Anticipating and adopting innovations in business-building digital and technology applications.

Manages Complexity

Making sense of complex, high quantity, and sometimes contradictory information to effectively solve problems.

Action Oriented

Taking on new opportunities and tough challenges with a sense of urgency, high energy, and enthusiasm.

Collaborates

Building partnerships and working collaboratively with others to meet shared objectives.

Communicates Effectively

Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences.

Self-Development

Actively seeking new ways to grow and be challenged using both formal and informal development channels.

Nimble Learning

Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodder.