Senior Data Engineer

Staff/Lead Data Engineer
Employment Type: Full-Time | Senior Individual Contributor
Hybrid, Central Belt Scotland.

We working exclusively on an exciting opportunity for a

Staff Data Engineer

to lead the technical design and implementation of our most critical data infrastructure and products. In this senior-level individual contributor role, you’ll be responsible for designing scalable systems, setting data architecture standards, and solving complex technical challenges that power analytics, data science, and business functions across the company.
You’ll collaborate with engineers, product managers, and business stakeholders to architect performant, reliable, and long-term data solutions that are customer-centric and business-aligned.

What You’ll Do:
Design and build scalable, reliable, and high-performance data systems.
Define and drive best practices for data modeling, ETL/ELT pipelines, and real-time streaming architectures.
Set technical direction and architectural standards across the data platform.
Work closely with cross-functional partners to meet evolving business and analytical needs.
Own complex technical systems end-to-end, from concept to production.
Advocate for engineering excellence and mentor other engineers on the team.

Technical Skills:
8+ years

of experience in data engineering or a related field, with a focus on building scalable data systems and platforms.
Strong expertise with modern data tools and frameworks such as

Spark ,

dbt ,

Airflow OR

Kafka ,

Databricks , and

cloud-native services

(AWS, GCP, or Azure).
Deep understanding of

data modeling ,

distributed systems ,

streaming architectures , and

ETL/ELT pipelines .
Proficiency in

SQL

and at least one programming language such as

Python ,

Scala , or

Java .
Demonstrated experience owning and delivering complex systems from architecture through implementation.
Excellent communication skills with the ability to explain technical concepts to both technical and non-technical stakeholders.

Preferred Qualifications:
Experience designing data platforms that support

analytics ,

machine learning , and

real-time operational workloads .
Familiarity with

data governance ,

privacy , and

compliance frameworks

(e.g., GDPR, HIPAA).
Background in

customer-centric

or

product-driven

industries such as

digital ,

eCommerce , or

SaaS .
Experience with

infrastructure-as-code

tools like

Terraform

and expertise in

data observability and monitoring

practices.

Shortlisting this week....