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

Apply Now

Azure Data Engineer Lead

Square One Resources
London
6 months ago
Applications closed

Related Jobs

View all jobs

Azure Data Engineer - Migration & Data Pipelines

Senior Azure Data Engineer - Cloud Data & Analytics Lead

Lead Data Engineer

Lead Data Engineer

Data Engineer

Sr. Data Engineer – Industry 4.0

Job Title:Azure Data Engineer Lead - Outside IR35
Location:Remote
Salary/Rate:£450 per day - Outside IR35
Start Date:28/04/2025
Duration:3 months

We have an exciting opportunity with a major retail company. They are looking for a Lead Azure Data Engineer to join on an initial 3 month contract working outside IR35 and fully remote.


Job Responsibilities/Objectives:

  1. Lead the design and execution of the end-to-end migration from on-premise data systems to Azure, ensuring scalability, reliability, and performance.
  2. Develop and optimise data pipelines using Azure Data Factory, Synapse Analytics, and related services to support data ingestion, transformation, and integration.
  3. Architect and implement Azure-based data solutions, including Data Lake, SQL Database, and Databricks, aligning with business and technical requirements.
  4. Establish cloud data engineering best practices, including governance, security, monitoring, and cost optimisation.
  5. Collaborate cross-functionally with cloud architects, analysts, and stakeholders to translate business needs into technical data solutions.
  6. Lead and mentor a team of data engineers, providing hands-on technical guidance, code reviews, and fostering a high-performance culture.


Required Skills/Experience:
The ideal candidate will have the following:

  1. Proven experience leading data engineering projects, especially cloud migration initiatives.
  2. Hands-on experience with Python, PySpark, SQL, and Scala.
  3. Deep knowledge of modern data architecture, data modeling, and ELT/ETL practices.
  4. Strong grasp of data security, governance, and compliance in the cloud.


If you are interested in this opportunity, please apply now with your updated CV in Microsoft Word/PDF format.


Disclaimer:
Notwithstanding any guidelines given to the level of experience sought, we will consider candidates from outside this range if they can demonstrate the necessary competencies.


Square One is acting as both an employment agency and an employment business, and is an equal opportunities recruitment business. Square One embraces diversity and will treat everyone equally. Please see our website for our full diversity statement.

#J-18808-Ljbffr

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.

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

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.