Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Big Data Software Engineer

Rapid7
Belfast
1 year ago
Applications closed

Related Jobs

View all jobs

Machine Learning Engineer (Databricks)

Data Scientist / Software Engineer

Lead Software Data Engineer – GraphQL, AWS & GoLang

Lead Data Scientist

Lead Data Scientist - Healthcare

Staff Machine Learning Engineer - Autonomy

About the Team

The Rapid7 Data Platform is a unified, integrated platform powered by Rapid7’s product suite providing our customers enhanced visibility into their attack surface, operational efficiency, risk management, and decision-making capabilities. 

Our teams are responsible for consolidating data from all Rapid7 products, transforming it for optimised retrieval, and ensuring high-performance and seamless access to our customers. This role is crucial to the platform’s success as it focuses on building a highly scalable and reliable data mesh that powers cross-product use cases through a distributed query engine for big data analytics.

About the Role

We are seeking an innovative, self-motivated Data and Performance Engineer who will act as a technical leader to collaborate with our product teams to optimise their data pipelines and retrieval processes for performance and efficiency. You will work with the Data Platform teams to implement monitoring and testing strategies to ensure the performance of the data and their queries as well as identify optimisations.

Technologies you will work with:

Trino

Iceberg

Parquet

Spark

Airflow

Kafka

AWS services such as Glue, S3, EKS

In this role, you will:

Analyse and optimise distributed SQL queries to improve performance

Suggest optimisations to our data pipelines

Provide recommendations for efficient partitioning strategies and schema designs

Conduct performance tuning for the data pipelines and queries

Develop performance monitoring strategies and tools

The skills you'll bring include:

5+ years of hands-on software engineering experience, with a specific focus on database query optimization

Strong database system expertise in query execution planning, query optimization, performance tuning, parallel computing, and schema design

Experience in continuously monitoring and optimising data pipelines for performance and cost-effectiveness

Ability to design, develop, implement, and operate highly reliable large-scale data lake systems in cooperation with product teams

Skills to analyse and performance test the data mesh performance and scalability, identify bottlenecks, recommend and develop improvements

Mentorship and guidance of junior engineers, providing technical leadership and fostering a culture of continuous improvement and innovation

Excellent verbal and written communication skills.

Strong, creative problem solving ability.

Nice to haves:

Trino/Presto data-mesh

AWS, Terraform, Kubernetes

Java

Kafka

We believe the best ideas and solutions come from diverse teams. If you're excited about this role and feel your experience can make an impact, don't hesitate – apply today!

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.