Data Engineer

Warrington
3 days ago
Create job alert

Focus 5 Recruitment are working with an exciting software business to help recruit a Data Engineer. The company have just been awarded 2 large contracts with international Mobile Network Operators. Appointed to help them source a Data Engineer, we’re looking for an experienced Data Engineer to design and optimize our client’s data pipelines and storage solutions.
This is an amazing opportunity to work with a growing and ambitious software business who have contracts with some of the world’s leading mobile network companies. They are looking for candidates who can come in at a key point in their growth and develop their career as they grow.
Key responsibilities for the Data Engineer –

  • Design and build high-performance, low-latency data pipelines capable of processing large volumes of data at high speed.
  • Develop and enhance real-time and batch data processing architectures.
  • Manage both structured and unstructured data, ensuring efficient ingestion, transformation, and storage.
  • Deploy scalable data storage solutions across bare metal and cloud platforms (AWS).
  • Optimize databases, data lakes, and messaging systems for maximum throughput and minimal latency.
  • Collaborate with DevOps and software engineering teams to maintain seamless data integration and flow.
  • Implement monitoring, logging, and alerting systems to track data pipeline performance and integrity.
  • Uphold data security and compliance across all environments.
    Data Engineer experience we’re looking for -
  • Demonstrated expertise in designing and deploying data architectures for high-velocity, high-throughput systems.
  • Strong proficiency in real-time data streaming technologies such as Kafka, Pulsar, and RabbitMQ.
  • Extensive experience with high-performance databases, including PostgreSQL, ClickHouse, Cassandra, and Redis.
  • In-depth knowledge of ETL/ELT pipelines, data transformation, and storage optimization.
  • Skilled in working with big data frameworks like Spark, Flink, and Druid.
  • Hands-on experience with both bare metal and AWS environments.
  • Strong programming skills in Python, Java, and other relevant languages.
  • Proficiency in containerization technologies (Docker, Kubernetes) and infrastructure as code.
  • Solid understanding of data security, encryption, and compliance best practices.
    Preferred Qualifications -
  • Experience working with telecom or financial systems.
  • Background in government or defence-sector projects.
    This is an exclusive role with a key client. For immediate consideration and full details, please submit an application ASAP

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

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 Leadership for Managers: Strategies to Motivate, Mentor, and Set Realistic Goals in Data-Driven Teams

Machine learning (ML) has become an indispensable force in the modern business world, influencing everything from targeted marketing campaigns to advanced medical diagnostics. As industries integrate predictive algorithms and data-driven decision-making into their core operations, the need for effective leadership in machine learning environments has never been greater. Whether you’re overseeing a small team of data scientists or spearheading an enterprise-scale ML project, your leadership style must accommodate rapid innovation, complex problem-solving, and diverse stakeholder expectations. This guide provides actionable insights into how you can motivate, mentor, and establish achievable goals for your machine learning teams—ensuring they thrive in data-driven environments.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.