Lead Data Engineer - SC Cleared

Fynity
London
1 year ago
Applications closed

Related Jobs

View all jobs

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer

Lead Data Engineer – SC Cleared (or Clearable)

Location:London

Salary:Up to £80,000

Start Date:ASAP



About the Role

Join a dynamic Digital Transformation Consultancy as a Lead Data Engineer and play a pivotal role in delivering innovative, data-driven solutions for high-profile government clients. You’ll be responsible for designing and implementing robust ETL pipelines, leveraging cutting-edge big data technologies, and driving excellence in cloud-based data engineering.



This role offers the opportunity to work with leading technologies, collaborate with data architects and scientists, and make a significant impact in a fast-paced, challenging environment.



Key Responsibilities:

  • Design, implement, and debug ETL pipelines to process and manage complex datasets.
  • Leverage big data tools, including Apache Kafka, Spark, and Airflow, to deliver scalable solutions.
  • Collaborate with stakeholders to ensure data quality and alignment with business goals.
  • Utilize programming expertise in Python, Scala, and SQL for efficient data processing.
  • Build data pipelines using cloud-native services on AWS, including Lambda, Glue, Redshift, and API Gateway.
  • Monitor and optimise data solutions using AWS CloudWatch and other tools.



What We’re Looking For:

  • Experience:Deep background in data engineering with hands-on expertise in big data technologies.
  • Cloud Expertise:Proven experience implementing pipelines using AWS services.
  • Technical Skills:Strong command of Python, Scala, SQL, and ETL tools.
  • Security Clearance:Candidates must have or be eligible for SC clearance. Preference will be given to those already SC Cleared.



SC Clearance Criteria:

  • Must be a British Citizen or have resided in the UK for at least 5 consecutive years.
  • Detailed employment history for the past 10 years or longer may be required.



Why Join Us?

  • Be part of a forward-thinking consultancy driving digital transformation for industry leaders.
  • Work with the latest big data and cloud technologies.
  • Collaborate with a team of skilled professionals in a fast-paced and rewarding environment.



If you’re passionate about delivering impactful data solutions and meet the criteria for this role, we’d love to hear from you. Apply today and lead the way in digital transformation!

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.

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.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.