Senior API Developer (Python & AWS)

Lichfield
1 month ago
Applications closed

Related Jobs

View all jobs

Quantitative Developer (python/react)

Full Stack Developer (Python and React) - Quantitative Analytics Team I Greenfield

Senior Data Engineer

Software Engineer

Senior Azure/Dynamics 365 Technical Lead

Senior Test Lead Engineer | Network Services

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

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.