Senior / Lead Data Engineer – Eligible for SC AWS or Azure

Avanti Recruitment
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior/Lead Data Engineer

Senior / Lead Data Engineer

Senior SAS Data Engineer - SC Cleared

Senior SAS Data Engineer - SC Cleared

Senior SAS Data Engineer - SC Cleared

Lead Data Engineer

Senior / Lead Data Engineer – Consultancy – Eligible for SC Clearance – AWS or Azure - LondonI’m looking for an experienced Senior / Lead Data Engineer to join a successful, multinational Consultancy in their London office working on high profile client projects.As a Senior Data Engineer, you'll design and implement cutting-edge data solutions that transform their clients' businesses. You'll work with cross-functional teams to create scalable, efficient architectures that turn complex data challenges into opportunities for innovation.Your role * Design end-to-end data architectures that align with business objectives * Create cloud-native solutions leveraging PaaS, serverless, and container technologies * Build robust data pipelines for both batch and streaming processes * Collaborate with clients to understand their data landscape and requirements * Mentor team members and champion best practices in data architectureTo be considered you will be able to demonstrate skills and experience in many of the following: * Expertise in designing production-grade data pipelines using Python, Scala, Spark, and SQLDeep knowledge of either: * AWS (EMR, Glue, Redshift, Kinesis, Lambda, DynamoDB) * Or * Azure (Data Factory, Synapse, Databricks, Event Hubs, Logic Apps, Cosmos DB) * Experience with data processing across structured and unstructured sources * Strong scripting abilities and API integration skills * Knowledge of data visualization and reporting best practicesDesirable but not essential: * Experience with data mining and machine learning * Natural language processing expertise * Multi-cloud platform experienceThey will with an Agile environment with Scrum practices, Cross-functional collaborative teams and need someone who can work from the London office or client sites 2 days a week.Salary: £80,000 - £100,000 + 25 days holiday (option to buy 5 more) + pension + Performance Bonus + share optionsLocation: Hybrid working – 2 days a week in the London office or on Client siteSC Clearance Eligibility – you must be eligible for SC Security Clearance (or higher) – this means at least 5 years residence in the UK and in that time you’ve not been out the country for more than 29 days consecutively and no more than 6 months out the country per year

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.