Azure Data Engineer

Birmingham
1 week ago
Applications closed

Related Jobs

View all jobs

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer - Insurance Firm – London – hybrid working

Azure Data Engineer - ADF, Snowflake - £425pd inside IR35

Azure Data Engineer

Azure Data Engineer

Azure Data Engineer

Annual Salary: £50k, depending on experience
Location: Birmingham
Job Type: Permanent, Hybrid (1-2 days per week in the office)My client is seeking a Azure Data Engineer to join their Digital & Technology team. This pivotal role reports directly to the Technical Delivery Manager and is focused on enhancing data architecture and governance across our Cloud platforms. As a Cloud Data Manager, you will be instrumental in designing, implementing, and managing data solutions to leverage cloud technologies effectively within the organisation.

Day-to-day of the role:

Maintain strong collaborative relationships with the Infrastructure and Research & Statistics teams.
Design and implement data storage strategies using Microsoft Azure's suite of storage solutions, including Azure SQL Database, Azure Data Lake Storage, and Azure Blob Storage.
Develop and maintain robust data pipelines for efficient data ingestion, transformation, and processing from various sources.
Oversee the implementation and management of data storage solutions, ensuring optimal performance, security, and compliance.
Manage data processing workflows and tools to extract insights and derive value from large datasets.
Facilitate seamless integration of data across systems and applications to enable cross-functional analysis and reporting.
Continuously monitor and optimise data solutions to enhance performance, reliability, and cost-effectiveness.
Implement security best practices and ensure compliance with relevant data protection regulations (e.g., GDPR) and industry standards.
Lead and mentor a team of DBAs and analysts, fostering a culture of collaboration, innovation, and continuous improvement.
Engage internal stakeholders to understand their data requirements and provide strategic guidance on leveraging cloud data services effectively.

Required Skills & Qualifications:

Proven experience in designing, implementing, and managing data solutions on cloud platforms.
In-depth knowledge of Azure data services, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, and Azure SQL Database.
Demonstrated leadership skills with a track record of communicating clear strategies and plans, giving direction, and motivating teams.
Ability to create standards involving database architecture and governance, communicating, and securing buy-in from senior stakeholders.
Experience in maintaining the security, confidentiality, and integrity of information systems through compliance with relevant legislation and regulations.
Ability to communicate complex technical concepts to a non-technical audience, building trust, engaging, and managing expectations of stakeholders at all levels.
Regular assessment of project progress to remove bottlenecks and improve the flow of the end-to-end delivery process.To apply for the Azure Data Engineer position, please submit your CV and cover letter detailing your relevant experience and why you are interested in this role

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.

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.