Data Engineer

Rapid7
Belfast, Northern Ireland
21 months ago
Applications closed

Related Jobs

View all jobs
Spotlight

Machine Learning Engineer - National Security (Gloucestershire)

Mind Foundry Gloucester, Gloucestershire, United Kingdom
On-site Clearance Required

Data Engineer

Relation Therapeutics London, United Kingdom
Permanent

Data Engineer, Strategic Account Services

Amazon London, United Kingdom
Permanent

Senior Data Engineer, Core Experimentation

OpenAI United Kingdom
£293,000 – £325,000 pa Hybrid

Senior Data Engineer

Synthesia London, United Kingdom
Hybrid

Senior Research Engineer - Data

Synthesia London, United Kingdom
Remote

Senior Simulation Data Engineer

PhysicsX London, United Kingdom
Posted
21 Aug 2024 (21 months ago)

Data Engineer II


Rapid7 seeks a highly motivated and inquisitive aspiring Data Engineer II to join our quickly scaling data engineering function. Come and join our efforts in unlocking the value of data through industry-leading innovation, cutting edge modern tooling, democratization at scale and building exceptional and trusted data products for the company! 

About the Team


As we spearhead a cultural shift to a data-driven business, Data Engineering serves as the Hub for all teams at Rapid7 from ML Ops, to Sales and Operations to Platform and Engineering. Our team is a highly skilled yet egoless group of data magicians (and humorists) with a penchant for innovation and a knack for problem solving. 

About the Role


The Data Engineering practice is growing quickly and we’re investing in a bright, data-focused future. We are seeking an aspiring data engineer to flourish and grow within our team. The ideal candidate has a solid foundational understanding of data engineering and software development concepts and best practices with some hands on experience preferred. Bring your courage, curiosity, problem solving skills, and technical chops!

In this role, you will:

Build and maintain pipelines and infrastructure that ingest, analyze and store Rapid7's enterprise data using modern tools such as Snowflake, Airflow, dbt and AWS

Work closely with senior engineers to drive software lifecycle including hands-on development, testing, deployment, and documentation

Participate in scrum events include sprint planning, retrospectives and daily stand-ups

Productionize data through dev ops processes (such as CICD) using containerization tools such as ECS

Collaborate with stakeholders in product, business and IT to deliver high quality data products and assist with data-related technical issues

Support large scale projects including major implementations, process improvements, and cross-function data initiatives 

The skills you’ll bring include:

BS in Computer Science, Analytics, Statistics, Informatics, Information Systems or 

another quantitative field or equivalent experience; Should have broad knowledge of core computer science / software engineering concepts.

2-3 years of experience in a data-focused required; specifically as a Data Engineer or highly technical Analytics Engineer

SQL fluency and data warehousing understanding required; Working experience with a programming language is highly preferred

Working knowledge with modern data tools such as Snowflake, dbt, Airflow, and AWS

Capable of taking well-defined tasks and completing these tasks with minimal supervision

General understanding of the SDLC including modern dev ops tools, code reviews, testing, and planning

Strong work ethic, resiliency, persistence, and urgency; Data Engineering holds itself to a high standard so you’ll need to keep up!

Sharp business and interpersonal skills; Should be able to effectively communicate status and escalate blockers

Be a team-player! Data Engineering has a nice balance of independent vs codependent - One Moose!



We know that the best ideas and solutions come from multi-dimensional teams. That’s because these teams reflect a variety of backgrounds and professional experiences. If you are excited about this role and feel your experience can make an impact, please don’t be shy - apply today.

 

Industry Insights

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

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Where to advertise machine learning jobs UK in 2026: the specialist boards and communities that reach ML, MLOps and deep learning engineering talent. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Machine Learning Jobs UK 2026: What to Expect Over the Next 3 Years

Machine Learning Jobs UK 2026: roles, salaries and the MLOps, LLM and generative AI hiring trends shaping UK ML careers over the next three years. Machine learning has undergone a transformation that few technology disciplines can match. In the space of three years it has moved from a specialism sitting at the edges of most organisations' technology strategies to a capability that sits at the centre of them. The tools have changed, the expectations have shifted, and the range of industries treating machine learning as a core business function — rather than an experimental one — has expanded dramatically. For job seekers, this creates both opportunity and complexity in roughly equal measure. The machine learning jobs market of 2026 is significantly larger than it was three years ago, but it is also significantly more demanding. Employers have developed more sophisticated expectations, the technical bar for specialist roles has risen, and the landscape of tools, frameworks, and architectural patterns that practitioners are expected to know has broadened considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what machine learning engineers and researchers are expected to build, and how the definition of a machine learning career is evolving beyond the model-building core toward a much wider range of roles across the full ML lifecycle. This article breaks down what the UK machine learning jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.