Senior API Developer (Python & AWS)

Lichfield
1 year ago
Applications closed

Related Jobs

View all jobs

2x Senior Data Engineer (Financial Services)

Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Scientist

Senior API Developer (Python & AWS) - Outside IR35 contract

API development with NetSuite integration

Must be open to travel to Lichfield around once per month

Working alongside a team of Data Engineers - must have knowledge to be able to collaborate. Big integration of Netsuite coming up (CRM & Financials)

Responsibilities

Working within an AGILE based team structure to plan and support definition, coding and deployment of Java, Java Script, Rest based APIs within an efficient and scalable software delivery pipeline to create domain data services within principles and practices of MACH
Identify, develop, document, deliver and modify high-performance APIs and programs using Java and Amazon Web Services (AWS)
Monitor API performance and promptly troubleshooting issues.
Participate in or lead functional, regression and load testing as defined in the test specifications, including event logging, and reporting of results.
Manipulate data, automate tasks and perform complex analysis using programming languages such as Python, R and SQL
Configure and manage a secure AWS infrastructure, including EC2, API gateways, containerisation technologies like Docker, orchestration tools such as Kubernetes and Relational Database services necessary to support a continuous integration/delivery environment, using principles and practices of infrastructure-as-code (IAC).Key Skills and Experience

Extensive Python development experience (Django framework)
Extensive experience with AWS native services such as Lambda, S3, API Gateway, SQS, SNS, CloudWatch, DMS, RDS and CloudFormation.
Strong proficiency in API integration, event-based architectures, microservices, and data products.
Comfortable working with AWS native CI/CD tools (e.g., AWS CodeCommit, CodeDeploy, etc.) and sprint management and documentation tools (e.g., Jira, Confluence).
Strong understanding of AWS networking, infrastructure and security.
Excellent verbal/written communication and teamwork skills suitable for a fast-paced, agile, and collaborative development environment.
Strong SQL knowledge and experience designing and managing data models.
Proficiency in AWS Glue and related AWS services to manage data pipelines, automate ETL workflows, and integrate datasets for reporting and dashboard creation.
Experience extracting and transforming complex data sets (ETL process design and administration).
Experience of integrating bespoke solutions with 3rd Party SaaS and PaaS services, e.g. Netsuite, Oracle Cloud, Boomi, etc.Please apply asap if interested

GleeIT

At Gleeson Recruitment Group, we embrace inclusivity and welcome applicants of all backgrounds, experiences, and abilities. We are proud to be a disability confident employer.

By applying you will be registered as a candidate with Gleeson Recruitment Limited. Our Privacy Policy is available on our website and explains how we will use your data

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.

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.