Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer

RES
Kings Langley
8 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Description

Do you want to work to make Power for Good?We're the world's largest independent renewable energy company. We're guided by a simple yet powerful vision: to create a future where everyone has access to affordable, zero carbon energy.We know that achieving our ambitions would be impossible without our people. Because we're tackling some of the world's toughest problems, we need the very best people to help us. They're our most important asset so that's why we continually invest in them.RES is a family with a diverse workforce, and we are dedicated to the personal professional growth of our people, no matter what stage of their career they're at. We can promise you rewarding work which makes a real impact, the chance to learn from inspiring colleagues from across a growing, global network and opportunities to grow personally and professionally.Our competitive package offers a wide range of benefits and rewards.The positionThe Data Engineer will play a crucial role in designing, developing, testing, and maintaining data solutions.The primary responsibility for this role will be to ensure the efficient flow of data across systems, enabling data-driven decisions making and insight generation. They partner with the business and departmental specialists to support, troubleshoot, and implement features and functionality of the applications in their areas of responsibility. The data engineer provides efficient and consistent use of data technologies throughout RES Americas and coordinates with other IT functions across the globe to ensure standardization of support and processes.AccountabilitiesProvides timely and quality resolution support through troubleshooting, research, and resolution. Assist in planning and consulting on how to effectively deliver designs, models, and ETL pipelines within the organization. Develops and designs ETL pipelines, contributes to logical data models, and coordinates with users the development and delivery of reporting and integration solutions. Assesses and improves the operational health of the data solutions including security, availability, performance, interoperability, and reliability. Implements data governance policies and security to ensure compliance and safe guard data assets. (HIPPA, GDPR, GAAP) Partners with functional leaders to identify strategic objectives, determine functional needs and requirements, and craft comprehensive plans for continuous data solution development aligned with those goals and needs. Independently tests, debugs, and documents enhancements to the data platform. Authors and routinely reviews technical documentation necessary to facilitate usage and adoption of applications, including user and admin guides; routinely review documentation to ensure accuracy. Identifies trends in customer issues, recommends improvements, and implements approved improvements. Writes custom reports and SQL queries. Presents and communicates with management on the evaluation of the current solution, proposed solution, and the optional and recommended next steps.Additional ResponsibilitiesMentors and coaches' other application support resources within their area of expertise. Assumes responsibilities for additionally assigned assignments related to supported data engineering solutions. Presents, supports, and leads by example with a safety and quality-oriented attitude. Ability to assess and work with the business to obtain business requirements and understand the business needs. Attends work regularly and punctually, as scheduled or expected. Complies with Employee Handbook, Code of Conduct, and Company Policies & Procedures.Knowledge, Skills & AbilitiesDemonstrated experience in developing and maintaining enterprise-level data solutions. Experience in developing solutions for Business Intelligence reporting. Knowledge of Data modeling methodologies Inmon/Kimbal. Proficient in SQL and Python. Knowledge of software development lifecycle. Experience troubleshooting issues and optimizing performance in a cloud environment. Experience with Microsoft Synapse, SQL Server, Azure Data Factory and related technologies. Knowledge of help desk ticketing software, preferably ServiceNow. Proficient in Microsoft Office. Familiarity with ITIL v3 or related service delivery frameworks. Demonstrated experience in Project Management as a team member. Exceptional verbal and written communication. Critical thinking skills. Self-motivated and able to work under pressure.

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.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.