Principal Data Engineer

dotdigital
City of London
1 month ago
Applications closed

Related Jobs

View all jobs

Principal Data Engineer

Principal Data Engineer (GCP)

Principal Data Engineer (MS Azure)

Principal Data Engineer

Principal Data Engineer

Principal Data Engineer (GCP)

About Us

The Company: Dotdigital is a thriving global community of passionate, dedicated professionals, committed to the collective success of the organization and its clients. Our core principles of innovation, teamwork, and client-focused solutions drive us to approach challenges with a growth mindset and take ownership of our work. At Dotdigital, collaboration and curiosity pave the way for meaningful connections and learning opportunities with diverse peers. Our work environment encourages knowledge sharing, fosters exploration, and cherishes creative ideas. Combined, these guide us towards a shared vision in which brands around the world exceed customer expectations through the adoption of responsible marketing practices.


The Product: Dotdigital is an all-in-one customer experience and data platform (CXDP) that empowers marketing teams to exceed customer expectations with highly personalized cross-channel journeys. With Dotdigital, marketers can seamlessly unify, enrich, and segment customer data. Breaking down data silos, Dotdigital streamlines decision‑making and paves the way for marketing creativity that delivers customer engagement at scale. With powerful AI capabilities, Dotdigital makes it easy to automate deeply personalized experiences across web, email, SMS, WhatsApp, chat, push, social, ads, and more.


About the Role

We are on the lookout for a Principal Data Engineer to help define and lead the next generation of our data platform and data capabilities. You’ll play a key role in building scalable, resilient and intelligent data systems that power real‑time services, insights, products and decisions across Dotdigital.


As a Principal Data Engineer, you will be instrumental in driving the architecture, development and delivery of our data platform. You will lead key initiatives, provide technical direction and collaborate with product, analytics and data science teams to ensure data value is realised across the entire ecosystem. Working across the entire data lifecycle, you will help shape how data is collected, processed and consumed across Dotdigital.


Responsibilities

  • Lead the design and implementation of scalable, secure and resilient data systems across streaming, batch and real‑time use cases.
  • Architect data pipelines, model and storage solutions that power analytical and product use cases; using primarily Python and SQL via orchestration tooling that run workloads in the cloud.
  • Leverage AI to automate both data processing and engineering processes.
  • Assure and drive best practices relating to data infrastructure, governance, security and observability.
  • Work with technologists across multiple teams to deliver coherent features and data outcomes.
  • Support the data team to help adopt data engineering principles.
  • Identify, validate and promote new tools and technologies that improve the performance and stability of data services.

About You
Technical Expertise

  • Extensive experience delivering python‑based projects in the data engineering space.
  • Extensive experience working with SQL and NoSQL database technologies (e.g. SQL Server, MongoDB & Cassandra).
  • Proven experience with modern data warehousing and large‑scale data processing tools (e.g. Snowflake, DBT, BiqQuery, Clickhouse).
  • Hands on experience with data orchestration tools like Airflow, Dagster or Prefect.
  • Experience using cloud environments (e.g. Azure, AWS, GCP) to process, store and surface large scale data.
  • Experience using Kafka or similar event‑based architectures e.g. (Pub/Sub via AWS SQS, Azure EventHubs, AWS Kinesis).
  • Strong grasp of data architecture and data modelling principles for both OLAP and OLTP workloads.
  • Capable in the wider software development lifecycle in terms of agile ways of working and continuous integration/deployment of data solutions.

Engineering Leadership

  • Experience as a lead or Principal Engineer on large‑scale data initiative or product builds.
  • Demonstrated ability to architect data systems and data structures for high volume, high throughput systems.
  • Proven experience leading data platform modernisation or cloud migration projects.
  • Comfortable taking ownership of difficult data problems and driving them to resolution.

Bonus

  • Experience using ClickHouse as part of a data pipeline and analytics solution.
  • Experience using Databricks or similar data platforms.

Why Us

Don’t just take our word for it – hear what your future colleagues have to say about working in our team:


As a member of the Data Engineering team I have had the opportunity to work on a wide variety of data platforms, which not only broadens my knowledge base but also keeps me constantly engaged with evolving technologies. The team I work with is highly skilled team and truly inspiring. We motivate each other to innovate and excel in solving complex, large‑scale problems with multi‑terabyte datasets and high throughput rates. Moreover, Dotdigital embraces a relaxed and flexible work culture, ensuring the great balance between productivity and well‑being. If you seek an environment that fosters personal and professional growth, Dotdigital’s data team is the perfect match.


Interview Process

  • 15 min Screening Call with Talent Team
  • Stage 1: Role deep dive with hiring manager(s)
  • Stage 2: Technical interview with data team

Some of Our Global Benefits

  • Parental leave
  • Medical benefits
  • Paid sick leave
  • Dotdigital day
  • Share reward
  • Wellbeing reward
  • Wellbeing Days
  • Loyalty reward

DEI commitment

As an equal opportunities employer we are committed to equality in all its practices with regard to race, religion, national origin, age, sex, marital status, ancestry, physical or mental disability, veteran status or sexual orientation. If you have any additional requirements or adjustments to assist an application then please don’t hesitate to contact us and advise us how we can best support you.


#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.