National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Azure Data Engineering Lead - Law Firm - Remote

Etech Partners
Southampton
8 months ago
Applications closed

Related Jobs

View all jobs

Manager, Data Engineering

Azure Data Engineer

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

Data Engineering Manager

My client are a Global Law Firm and are seeking a Senior Azure Data Engineering Lead Remote-based but you will need to go on site one or two days a month to either their London, Birmingham or Manchester offices. As a senior data engineer, you will be expected to work autonomously, taking responsibility for the end-ot-end delivery of solutions on projects. Skills Required Developing and implementing ETL processes using Microsoft Fabric and its component Azure - solid experience required of the Azure Data ecosystem Azure Synapse Azure Data Lake/Data Bricks/Data Factory Develop CI/CD pipelines for automated build and deploy Be happy to act as a lead and mentor to the other Azure Data Engineers Responsibilities Providing technical guidance and support to team members, fostering a collaborative and innovative work environment. Collaborating with stakeholders to understand business requirements and translate them into technical solutions. Mentoring and coaching team members to improve skills in your field of specialism. Managing and securing structured and unstructured data flows from multiple sources and integrate them to create a unified and reliable data pipeline. Ensuring data quality and implement appropriate data governance practices. Implementing and enforcing security measures to protect sensitive data. Ensuring compliance with data protection regulations and industry standards. My client is looking to recruit URGENTLY, please send your CV in Word format to be considered for this great opportunity. Etech Partners needs to collect and use your personal information when you apply for a role. We understand that you care about your privacy, and we take that seriously. Our Privacy Notice describes our policies and practices regarding collection and use of your personal data. By applying for this job you accept the Privacy Policy.

National AI Awards 2025

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.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.