Job Description

At Arctech Innovation, we develop cutting-edge solutions at the intersection of science, technology, and health. From pioneering hardware/software products to specialised contract research services, our work spans three core verticals: pest control, animal health, and human health. We're a mission-driven team operating in a fast-paced environment, passionate about solving real-world problems with science-led innovation.

About the Role

We are looking for a

Lead Data Engineer

to join

Arctech Innovation

and take ownership of our data platform as we scale our product and research operations. This is a high-impact, hands-on role based in Edinburgh, with hybrid working flexibility.

You'll play a central role in shaping and operationalising our long-term data architecture, transforming ad hoc data handling into scalable, production-grade pipelines that power smart detection devices and R&D services. You'll also help define platform architecture beyond databases, including analytics layers and integrations with IoT systems.

This role would suit an experienced data engineer ready to step into more leadership responsibility -- someone who can combine day-to-day execution with strategic thinking, and who's excited by building from the ground up in a science-led scale-up environment.

Key Responsibilities

1. Data Infrastructure Design & Implementation

Build,

productionise

, and maintain robust, scalable ETL/ELT pipelines from diverse sources -- including IoT devices, lab experiments, and commercial datasets.

Design and implement modular, secure, and cost-effective

cloud-native data infrastructure

(e.g. AWS).

Architect data systems that support current use cases and scale for future applications in analytics, ML, and data sharing.

2. Automation & Platform Optimisation

Lead the automation of manual data workflows and establish clear pipelines for data ingestion, transformation, and storage.

Introduce monitoring, alerting, and data validation tools to ensure reliability and performance in production.

3. Analytics Enablement & ML Readiness

Build internal data products, tools, and APIs to support reporting, analytics, and research insight generation.

Work closely with the Product and Innovation teams to future-proof pipelines for machine learning and real-time applications.

4. Documentation, Mentorship & Best Practices

Maintain clear and well-structured documentation across data workflows and platform architecture.

Champion data engineering best practices and support internal teams with training, onboarding, and guidance.

Provide mentoring or informal leadership to junior team members as the data function grows.

5. Strategic Input & Technical Roadmapping

Collaborate with the CIO to shape the long-term data strategy and align infrastructure decisions with company priorities.

Contribute to decisions on tools, platforms, and team evolution -- including input into hiring processes for future data roles.

Key Requirements

5+ years of experience in data engineering, with demonstrable ownership of

production-grade data systems

.

Advanced proficiency in

Python

and

SQL

, including pipeline orchestration and transformation logic.

Deep experience with

cloud platforms

(e.g. AWS, Azure, or GCP) and infrastructure-as-code practices.

Strong grasp of

data architecture principles

, data modelling, and platform scalability.

Experience deploying and managing

operational data pipelines

, ideally in an environment that blends structured and semi-structured data.

Strong communicator with the ability to explain technical concepts to non-technical audiences.

Pragmatic, delivery-focused mindset with an eye on long-term scalability and maintainability.

Desirable:

Exposure to IoT data pipelines or sensor-based systems.

Experience in science or research-driven organisations.

Familiarity with ML operations (MLOps) or analytics tools (e.g. DBT, Airflow, Looker).

Experience contributing to or mentoring within a growing data team.

What We Offer

A leadership-track role in a mission-driven science and technology company.

Competitive salary (60-70k DOE) with generous holiday allowance.

Hybrid working with flexibility to work from home and our Edinburgh office.

Autonomy to design and scale a greenfield data infrastructure.

Opportunity to shape a platform that supports real-world impact in global health and sustainability.

How to Apply

To apply, please send your CV and a brief cover letter outlining your interest in the role and relevant experience. We are reviewing applications on a rolling basis and encourage early submissions.

Job Types: Full-time, Permanent

Pay: 60,000.00-70,000.00 per year

Schedule:

Monday to Friday
Ability to commute/relocate:

Edinburgh EH8 9BT: reliably commute or plan to relocate before starting work (required)
Experience:

Data Engineer: 7 years (required)
Work authorisation:

United Kingdom (required)
Work Location: Hybrid remote in Edinburgh EH8 9BT

Application deadline: 03/06/2025