Senior Data Engineer

Akkodis
Luton
5 days ago
Create job alert

Akkodis is a global leader in engineering, technology, and R&D, harnessing the power of connected data to drive digital transformation and innovation for a smarter, more sustainable future. As part of the Adecco Group, Akkodis combines the expertise of AKKA and Modis, with over 50,000 engineers and digital specialists across 30 countries in North America, EMEA, and APAC. Our teams bring extensive cross-sector knowledge in critical technology areas such as mobility, software services, robotics, simulations, cybersecurity, AI, and data analytics, enabling clients to tackle complex challenges in today’s rapidly evolving markets.


Scope:

Akkodis is launching a new technical delivery team to drive a UK national program in collaboration with key partners, designed to transform and future-proof the central government’s workforce. By leveraging cutting-edge technology, strategic partnerships, and a comprehensive SaaS-based platform, this program will create an advanced, candidate-centric experience tailored to meet tomorrow’s public sector skill demands.


This high-impact initiative offers a unique opportunity to join a team dedicated to building a scalable, data-driven recruitment ecosystem. Through redesigning, building, and rolling out a sophisticated Big Data system, our diverse roles span across architecture, project management, data analytics, development, and technical support, giving you the chance to shape a dynamic, next-gen digital infrastructure.


You’ll be integral to our mission of crafting a seamless, powerful platform that empowers the public sector with the talent to navigate an evolving digital landscape.


Role:

As part of this mission, the Data Engineer role focuses on the planning, execution, and management of data migration projects. Data Engineer are responsible for transferring data from legacy systems to new platforms, ensuring accuracy, consistency, and adherence to data integrity standards.


Analyse existing data structures and understand business requirements for data migration.

Design and implement robust data migration strategies.

Develop scripts and processes to automate data extraction, transformation, and loading (ETL) processes.

Work closely with stakeholders, including business users and IT teams, to ensure data requirements are met, and migrations proceed without disruption to business operations.


Responsibilities:

  • Plan, coordinate, and execute data migration projects within set timelines.
  • Design and build ETL solutions, ensuring data quality and integrity throughout the migration process.
  • Troubleshoot and resolve data-related issues promptly to minimise disruption.
  • Collaborate with various teams to align migration processes with organisational goals and regulatory standards.


  • Proficiency in AWS ETL technologies, including Glue, Data Sync, DMS, Step Functions, Redshift, DynamoDB, Athena, Lambda, RDS, EC2 and S3 Datalake, CloudWatch for building and optimizing ETL pipelines and data migration workflows.
  • Working knowledge of Azure data engineering tools, including ADF (Azure Data Factory), Azure DB, Azure Synapse, Azure Data lake and Azure Monitor providing added flexibility for diverse migration and integration projects.
  • Prior experience with tools such as MuleSoft, Boomi, Informatica, Talend, SSIS, or custom scripting languages (Python, PySpark, SQL) for data extraction and transformation.
  • Prior experience with Data warehousing and Data modelling (Star Schema or Snowflake Schema).
  • Skilled in security frameworks such as GDPR, HIPAA, ISO 27001, NIST, SOX, and PII, with expertise in IAM, KMS, and RBAC implementation.
  • Cloud automation and orchestration tools like Terraform and Airflow.
  • Strong analytical skills to assess data quality, identify inconsistencies, and troubleshoot data migration issues.
  • Understanding of database management systems (SQL Server, Oracle, MySQL and NoSQL) and SQL query optimisation.
  • Ability to plan and execute data migration projects, manage timelines, and coordinate with stakeholders.
  • Precision in handling large volumes of data and ensuring accuracy during migration processes.
  • Effective communication skills to convey technical concepts and updates to diverse audiences, including non-technical stakeholders.
  • Cloud certifications like AWS and Azure are preferred.



Required Experience:

  • Proven experience in data migration, data management, or ETL development.
  • Experience working with ETL tools and database management systems.
  • Familiarity with data integrity and compliance standards relevant to data migration.


Required education

Bachelor’s degree in Information Technology, Computer Science, Data Science, or a related field.

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior 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.

Rural-Remote Machine Learning Jobs: Finding Balance Beyond the Big Cities

Over the past decade, machine learning (ML) has transformed from a niche research domain into a pervasive technology underpinning everything from recommendation systems and voice assistants to financial forecasting and autonomous vehicles. Historically, the UK’s major tech hubs—particularly London—have been magnets for top ML talent and corporate headquarters. However, remote work has become mainstream, and many ML professionals are realising they can excel in their field while living far beyond the city limits. At MachineLearningJobs.co.uk, we’ve observed a growing interest in positions that allow for a rural lifestyle or a coastal environment, often reflected in search terms like “ML remote countryside” or “tech jobs by the sea.” This surge is no coincidence. Flexible work policies, better rural broadband, and the nature of machine learning tasks—much of which can be done through cloud platforms—are bringing new opportunities to those who wish to swap urban hustle for fresh air and scenic views. Whether you’re a data scientist, ML engineer, researcher, or product manager, a rural or seaside move could reinvigorate your work-life balance. In this article, we’ll unpack why rural-remote ML jobs are on the rise, how you can navigate the challenges of leaving the city, and what you need to do to thrive in a machine learning career beyond the M25. If you’ve dreamt of looking up from your laptop to rolling fields or ocean waves, keep reading—your rural ML role might be closer than you think.

Quantum-Enhanced Machine Learning—Propelling AI into the Next Frontier

Machine learning (ML) has revolutionised how we interpret data, build predictive models, and create intelligent applications. From recommendation engines and self-driving cars to advanced genomics and natural language processing, ML solutions are integral to nearly every corner of modern life. However, as data complexity and model size continue to skyrocket, the computational demands placed on ML systems grow in tandem—often pushing even high-performance classical computers to their limits. In recent years, quantum computing has emerged as a tantalising solution to these challenges. Unlike traditional digital systems, quantum computers exploit quantum mechanics—superposition and entanglement—to process information in ways that defy conventional logic. As these machines mature, they promise exponential speed-ups for certain tasks, potentially reshaping how we approach AI and data-intensive challenges. What does this mean for machine learning? Enter quantum-enhanced ML, a new frontier where quantum processors and classical ML frameworks unite to accelerate model training, tackle high-dimensional data, and solve complex optimisation tasks more efficiently. In this article, we will: Unpack the current state of machine learning, highlighting key bottlenecks. Provide a concise overview of quantum computing—why it’s radical and how it differs from classical technology. Examine potential breakthroughs in quantum-enhanced ML, including real-world use cases and technical approaches. Explore the roles and skill sets that will define this quantum-AI era, with guidance on how to prepare. Discuss the roadblocks (like hardware maturity and ethical concerns) and how they might be addressed in the years to come. If you’re a machine learning engineer, data scientist, or simply an AI enthusiast fascinated by the next wave of computational innovation, read on—quantum computing could become an integral part of your future toolkit, opening up job opportunities and reimagining what ML can achieve.

Machine Learning Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Machine learning (ML) has become the beating heart of modern tech innovation, powering breakthroughs in healthcare, finance, cybersecurity, robotics, and more. Across the United Kingdom, this surge in ML-driven solutions is fueling the success of countless start-ups—and spurring demand for talented machine learning engineers, data scientists, and related professionals. If you’re eager to join a high-growth ML company or simply want to keep tabs on the latest trends, this Q3 2025 Investment Tracker will guide you through the newly funded UK start-ups pushing the boundaries of ML. In this article, we’ll highlight key developments from Q3 2025, delve into the most promising newly funded ventures, and shed light on the machine learning roles they’re urgently seeking to fill. Plus, we’ll show you how to connect with these employers via MachineLearningJobs.co.uk, a dedicated platform for ML job seekers. Let’s dive in!