Data Engineer (Contract)

JR United Kingdom; Slough; Remote; GBP 80,000 - 100,000; Full time

Job summary

A leading SaaS organization is seeking a Data Engineer for a 6-month contract role. The successful candidate will be responsible for designing web crawlers, building ETL pipelines, and performing data analysis to enhance data insights and support financial services. This predominantly remote position includes occasional office visits and offers a competitive daily rate.

Qualifications

• 3-5 years of experience in data engineering role.
• Proficient in Python, web scraping libraries (Scrapy, BeautifulSoup, Selenium).
• Experience with ETL/ELT pipelines and data analysis tools.

Responsibilities

• Design and maintain Python-based web crawlers.
• Build and maintain ETL pipelines.
• Collaborate with cross-functional teams for data-driven decision-making.

Skills

Data cleaning

Web scraping

Data analysis

Machine learning

SQL

Tools

Scrapy

BeautifulSoup

Selenium

Pandas

NumPy

Scikit-learn

TensorFlow

PostgreSQL

MySQL

AWS

Azure

GCP

Job description

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Data Engineer - Contract
£450-£500 per day | Outside IR35
6-Month Initial Contract
Predominantly Remote | Occasional Office Visits Required

We are working with a fast-growing SaaS organization that plays a key role in providing data-driven solutions across the financial services sector. As part of their mission to scale impactful products, they are looking to expand their data capabilities and optimize the quality and availability of insights across their platform.

This role is crucial for enhancing their current architecture, integrating diverse data sources, and enabling predictive and prescriptive analytics that will directly influence business strategy and client delivery.

Key responsibilities

Design, deploy, and maintain Python-based web crawlers using tools such as Scrapy, BeautifulSoup, or Selenium

Implement scalable and reliable web scraping frameworks for high-volume data extraction across websites and social media platforms

Perform data cleaning, standardization, and normalization to ensure consistency and quality across all datasets

Build and maintain ETL pipelines for processing structured and unstructured data

Conduct data analysis and modeling using tools like Pandas, NumPy, Scikit-learn, and TensorFlow

Leverage financial data expertise to identify trends, patterns, and anomalies within complex datasets

Support and improve SQL-based queries and work with database systems including PostgreSQL and MySQL

Collaborate with cross-functional teams, including data scientists, analysts, and product stakeholders, to support data-driven decision-making

Work with cloud environments such as AWS, Azure, or GCP, and explore opportunities to scale infrastructure

Required experience and skills

3-5 years of experience in a data engineering or similar role

Proficiency in Python for web crawling using libraries like Scrapy, BeautifulSoup, or Selenium

Strong understanding of data cleaning, standardization, and normalization techniques

Experience building ETL/ELT pipelines and working with large-scale data workflows

Hands-on experience with data analysis and machine learning libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow

Familiarity with SQL and relational database systems (e.g., PostgreSQL, MySQL)

Exposure to cloud platforms such as AWS, Azure, or GCP

Experience with big data tools such as Spark and Hadoop

Previous experience working with financial data, including understanding of financial metrics and industry trends