Data Engineer

Intec Select
Liverpool
8 months ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer - Consultancy - Up to £600 per day (Inside IR35) - 6 Month Contract - Remote


Overview:

Join a leading consultancy, delivering innovative data-driven solutions for global clients. You’ll play a key role in developing and supporting enterprise-grade data platforms and services, ensuring high-quality data pipelines and enabling smarter business decision-making.


Key Responsibilities:

  • Design and develop homogenous data repositories for enterprise reporting and analytics.
  • Ingest data from SQL databases, REST APIs, Kafka streams and other sources.
  • Apply data cleansing rules to ensure high data quality standards.
  • Model data into a single source of truth using Kimball methodology (star schema, snowflake, etc.).
  • Develop high-quality code following DevOps and software engineering best practices, including testing and CI/CD.
  • Monitor and maintain business-critical pipelines, reacting to and resolving failures when required.
  • Collaborate with the data team to refine backlogs, plan sprints and continuously improve workflows.
  • Perform ad-hoc data analysis across structured and unstructured data sources to support solution design.
  • Document datasets in the data catalogue, including ownership, lineage, sensitivity and definitions.
  • Ensure compliance with GDPR and other data regulations when handling sensitive information.
  • Support the stability and performance of enterprise data platforms.


Requirements:

  • Strong Azure data skills: Data Factory V2, Data Lake Storage V2, Databricks, Function Apps, Logic Apps, Stream Analytics, Terraform, Azure CLI/Portal/PowerShell.
  • Proficient with PySpark, Delta Lake, Unity Catalog and Python (including unit and integration testing).
  • Deep understanding of software development principles (SOLID, testing, CI/CD, version control).
  • Strong knowledge of Kimball data modelling.
  • Advanced SQL and data analysis skills.
  • Excellent written and verbal communication.
  • Proven ability to deliver under pressure while maintaining high standards.
  • Passion for technology and its impact on business outcomes.


Package:

  • Day Rate: Up to £600 per day. (Inside IR35)
  • Contract Basis: Fully Remote.
  • Consultancy environment: Innovative, fast-paced projects with cutting-edge technologies.


Data Engineer - Consultancy - Up to £600 per day (Inside IR35) - 6 Month Contract - Remote

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 Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.