SC Cleared Azure Data Engineer - Government client

Square One Resources
Newcastle upon Tyne
2 weeks ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

IT Support Engineer/MS Azure/Office365/Cloud/AWS/SC Cleared

Deployment Technician (SC Cleared or Clearable)

Data Engineer - SAP Data Services, Oracle, SQL, ETL - (SC Cleared)

Data Engineer - SAP Data Services, Oracle, SQL, ETL - (SC Cleared)

Data Engineer - SAP Data Services, Oracle, SQL, ETL - (SC Cleared)

Job Title:SC Cleared Azure Data Engineer - Government client - Fully Remote

Location:Fully Remote - UK Based

Salary/Rate:Up to £455 a day Inside IR35

Start Date:April / May

Job Type:3 Month Contract (with scope to extend)


Company Introduction


We are looking for an SC Cleared Data Engineer to join our client in the Government Administration sector.


**Candidates applying for this role must hold active Security Clearance**


As a senior data engineer, you would be engaging with data leads, data scientists, analysts and users around the data space for the data analytics, data insights development and implementation of this team. Engage with business analyst, data scientist , project and delivery leads in analysing backlogs, defining/redefining metric tickets, implementation logic, data mapping, related tasks creation and estimations. A strong actioner of data standards for ETL purposes , data modelling, best practices and strive for its implementation .


Required Skills/Experience


  • Should be strong in Azure data services like ADF, Synapse, SQL, ADB , etc..
  • Should be strong in Databricks notebooks development for data ingestion, validation, transformation and metric build.
  • Should be strong in PySpark and SQL.
  • Should be strong in ADF pipeline development, data orchestration techniques, monitoring and troubleshooting
  • Should be strong in stored procedure development.
  • Good knowledge in data modelling (dimensional) and Power BI reporting.


Job Responsibilities/Objectives


  • Analyse raw data (mostly in Json format ) for data parsing, schema evolution, data transformation towards metric development purpose.
  • Analyse reporting/metric requirements from data engineering perspective for refinement, estimation , development and deployment.
  • Closely work with analysts , data scientists to understand the business requirements, data sources and logic for metric development.
  • Create normalised/dimensional data models based on the requirement.
  • Translated and refine the notebooks and logics developed as part of prototype
  • Transform data from landing/staging/transformed to synapse dimensional model.
  • Creating notebooks in Databricks for incremental data load and transformation.
  • Creating stored procedures for data load and transformation in azure synapse dedicated pools
  • Created ADF pipelines for data orchestration across different data layers of data bricks and synapse


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 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.

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.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.