Principal Data Engineer

Arqiva; London; Hybrid; GBP 70,000 - 80,000; Full time

Job summary

A leading technology services company is seeking a Principal Data Engineer to spearhead the design of scalable cloud-based data platforms. This role demands expertise in AWS, Databricks, and real-time data processing, with an emphasis on mentoring teams and delivering robust data solutions. The position offers a hybrid work environment with competitive compensation and benefits.

Benefits

Up to £80K salary

10% bonus

6% pension contribution

Private Medical

25 days annual leave

Flexible benefits including discounts, wellness programs

Qualifications

• Deep expertise in AWS and cloud-native data solutions.
• Advanced experience with Apache Spark and Databricks for data processing.
• Strong capability in writing and optimizing SQL and Python code.

Responsibilities

• Design and deliver enterprise-scale data architectures on AWS.
• Build and manage robust ETL/ELT pipelines for data ingestion.
• Provide technical mentorship and thought leadership.

Skills

Python

SQL

PySpark

AWS

Databricks

Apache Spark

Data Pipelines

Cloud Computing

Tools

Docker

GitLab

Airflow

Kafka

Job description

Job Description

Location: We operate a flexible, hybrid working environment with the candidate required to travel to either our Winchester or London office once or twice a week.

We offer

• Up to £80K
• 10% bonus
• 6% pension contribution
• Private Medical
• 25 days annual leave
• Access to our comprehensive flexible benefits including discounts on big brands, wellness and employee assistance programmes, gymflex, buy and sell annual leave, travel and dental insurance
• Work. Life. Smarter. Our commitment to a flexible and hybrid working culture

Purpose

We're looking for a hands-on Principal Data Engineer to lead the design and development of scalable, secure cloud-based data platforms and pipelines that power enterprise analytics, reporting, and real-time decision-making.

This is a strategic and technical leadership role, ideal for someone with deep expertise in AWS, Databricks, Apache Spark, and Python/SQL, who can mentor teams, influence architecture, and deliver end-to-end data solutions across a modern tech stack.

Accountabilities

• Design and deliver enterprise-scale data architectures on AWS using services like S3, EMR, Glue, Redshift, Lambda, and IAM.
• Build and manage robust ETL/ELT pipelines supporting both batch and real-time data ingestion and transformation.
• Deploy and optimise Apache Spark jobs, leveraging Databricks and Delta Lake for distributed data processing.
• Lead the implementation of unified analytics workflows, integrating Databricks with the wider AWS environment.
• Write clean, efficient, and reusable code in Python, building production-ready data transformation scripts.
• Develop complex SQL queries across multiple RDBMS and cloud-native warehouses.
• Drive data quality, lineage, and governance standards across structured and unstructured datasets.
• Collaborate with data scientists, analysts, and business stakeholders to define and deliver scalable solutions.
• Provide technical mentorship and thought leadership to data engineers and wider delivery teams.
• Promote automation and operational efficiency through CI/CD, containerisation (e.g. Docker/ECS), and infrastructure as code.

Skills

• Python, SQL, PySpark, Scala, Java
• AWS (S3, Glue, Redshift, Lambda, EMR, IAM, ECS, SageMaker), Databricks, Delta Lake
• Apache Spark, Airflow, Dagster, Rundeck
• Kafka, Logstash, NiFi
• PostgreSQL, Oracle DB, MongoDB
• ELK Stack (Elasticsearch, Logstash, Kibana), Dynatrace, CloudWatch
• GitLab, CI/CD, Docker, Infrastructure as Code
• Agile/Scrum

Knowledge & Experience

• Senior/principal data engineering roles with hands-on leadership experience.
• Proven success in designing and deploying cloud-native data solutions, particularly on AWS.
• Advanced experience with Apache Spark, Databricks, and real-time data processing.
• Strong capability in writing and optimising complex SQL and Python code.
• Background in handling large-scale data transformations and integrating multiple data sources.
• Experience with data lakes, Delta Lake, and modern analytics platforms.
• Skilled in stakeholder engagement, mentoring engineers, and delivering high-quality solutions in fast-paced environments.
• A passion for simplifying complex problems and building future-proof data infrastructure.

We are the undisputed leader in UK TV and radio broadcast, and the UK's leading Smart utilities platform, directly shaping the future of connectivity.

Through our established infrastructure we ensure that media and data are delivered exactly where they're needed most, whether it's bringing content to your TV or radio or transmitting data from your smart meter to your utility provider - chances are our services are a part of your daily life, seamlessly connecting you through our behind-the-scenes technology.

With an impressive history and an innovative future ahead of us, leading the transition of global media distribution to cloud based solutions and creating scalable solutions for new connectivity sectors - you'll have many opportunities to develop and grow your unique career with us.

Why Arqiva? Reward . Connection . Growth

At Arqiva, we believe in supporting you to be your best, both at work and outside of it. That's why our rewards and benefits go far beyond your pay; take a look at our totalreward2025 booklet.

Here, you'll find endless opportunities to connect, whether that's with colleagues through our internal networks and events or by making a difference in the communities where we work.

And when it comes to your career, we're committed to helping you grow. Whether you want to become a specialist in your field or climb to the top, we'll support you every step of the way.

#LI-KM1