Data Engineer - Python / Data Science - London (Hybrid)

Square One Resources; London; Hybrid; GBP 150,000 - 200,000; Full time

Job summary

An established industry player is seeking a highly skilled Data Engineer to join their dynamic team in London. This role offers a unique opportunity to work on innovative data projects, leveraging your expertise in Python, SQL, and Azure. You will contribute to enhancing location inference models and developing data pipelines that drive actionable insights for clients. With a hybrid work model, you will enjoy flexibility while collaborating with a talented team. If you are passionate about data engineering and eager to tackle complex challenges, this is the perfect opportunity for you to make a significant impact.

Qualifications

• Strong Data Engineering and Data Science experience required.
• Proficient in Python and SQL with a strong statistical background.
• Experience with Microsoft Azure and large-scale data processing.

Responsibilities

• Develop algorithms to enhance location inference models.
• Design and validate concepts for visualizing population density.
• Build and optimize data pipelines for efficiency.

Skills

Data Engineering

Data Science

Python

SQL

Microsoft Azure

Git

Statistical Analysis

Geospatial Data

Problem Solving

Communication Skills

Tools

GeoPandas

QGIS

PostGIS

Tableau

Power BI

Databricks

Job description

Job Title: Data Engineer - Python / SQL - London (Hybrid)
Location: Paddington (2 x day per week in London)
Salary/Rate: £490
Start Date: May 2025
Job Type: Contract (Inside IR35)

Company Introduction:

Our client is an industry leading UK telecommunications company who are currently recruiting for a highly skilled Data Engineer / Data Consultant with Data Science, Python, SQL & Azure experience for a 12-month contract.

Strong Data Consultancy experience is also required for this role.

Working two days per week in the London, Paddington office.

Required Skills/Experience:

1. Strong Data Engineering / Data Consultant experience
2. Data Science experience
3. Engineering experience
4. Strong experience in writing, deploying, and optimising code (Python, SQL, or equivalent).
5. Extensive experience creating and implementing methodologies/algorithms in an automated workflow.
6. Experience with Microsoft Azure
7. Deep understanding of databases and ability to write efficient analytical queries.
8. Hands-on experience in developing, testing, and deploying complex data models and methodologies.
9. Proficiency with Git for version control and collaboration.
10. Strong statistical and mathematical background with an ability to apply advanced analytics to real-world data challenges.
11. Experience with large-scale data processing
12. Ability to work with geospatial data and spatial analysis techniques.
13. Strong business awareness and aptitude for building and improving data products.
14. Self-motivated with excellent problem-solving, organisational, and time management skills.
15. Excellent written and spoken communication skills.
16. Must be available to interview the week commencing 19th of May (And ideally start the week commencing the 26th of May)


Desirable Skills/Experience:

1. GIS experience and proficiency with geospatial libraries (e.g., GeoPandas, QGIS, PostGIS).
2. Familiarity with Databricks and distributed computing frameworks (e.g. Spark).
3. Exposure to CI/CD pipelines and workflow automation.
4. Experience with data visualisation tools such as Tableau, Power BI, or equivalent.
5. Knowledge of deploying machine learning models into production environments.

Key Accountability's and deliverable:

1. Enhancing Location Inference Models: Develop and refine algorithms that improve the accuracy and precision of inferred user locations using MND data.
2. Localised Population Density Insights: Design, prototype, and validate a concept for understanding and visualising population density at a granular level using mobile network data.
3. Data Pipeline Development & Optimisation: Work with engineers to build and optimise data pipelines, ensuring efficiency and scalability.
4. Continuous Improvement: Drive methodological advancements and improvements in data processing and modelling practices.
5. Customer-Centric Approach: Ensure outputs align with business needs, providing actionable insights to customers and stakeholders.
6. Technical Support & Issue Resolution: Respond to technical challenges efficiently, ensuring data integrity and consistency.


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.