Senior Data Engineer - Local Government

Salt
Ruislip
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer - Databricks

Senior Data Engineer - DV Cleared

Senior Data Engineer - MS Fabric - Remote - £70k - £75k

Job Title: Data Engineer - Local GovernmentLocation: Central London (Hybrid - 1-2 days onsite per week)Contract: 3-Month Rolling (Extensions Expected)Rate: £428 per day (Inside IR35)Start Date: 31st March 2025Join a Forward-Thinking Local Government TeamSalt is proud to be working with a high-profile Local Government body in Central London that is committed to digital innovation and data-driven decision-making. As part of their Smart City initiative, they are expanding their data capabilities to drive service transformation and operational efficiency.We are looking for a Data Engineer to join their product team, playing a key role in designing and developing scalable, high-quality data solutions that enhance public services.What You'll Be Doing:Designing, building, and optimising scalable data pipelines and architecturesEnsuring high data quality, accessibility, and integrity across internal and external datasetsDeveloping and maintaining data products that generate valuable insightsWorking with modern cloud-based data technologies , including Azure Data Factory, Synapse, and SnowflakeImplementing dimensional data models and working with SQL, NoSQL, and time-series databases (InfluxDB)Using Python for data pipeline development and visualisationDeploying applications via Docker and contributing to CI/CD pipelinesWhat We're Looking For:Extensive experience in Data Engineering , particularly building scalable, reusable cloud-based data pipelinesStrong expertise in Azure Data Factory, Synapse, and SnowflakeProficiency in Python, SQL, and NoSQL databases , with experience in time-series databases like InfluxDBKnowledge of dimensional modelling and experience deploying applications using DockerFamiliarity with CI/CD operating models and best practices in data engineeringA strong background in Government or Public Sector projects is highly desirableWhy Apply?Be part of a cutting-edge Smart City transformationWork on impactful projects that enhance services for millions of residentsLong-term contract potential with rolling extensionsHybrid working model with a mix of remote and onsite collaboration in Central London*Rates depend on experience and client requirements

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.

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.