Python Developer

Battenhall
London
1 week ago
Applications closed

Related Jobs

View all jobs

Python Developer

Python Developer - Digital Transformation Team

Python Developer

Python Developer

Python/Data Science Developer

Python/Data Science Developer

Python Developer, UK


Role Summary:

The role of Python Developer will be part of Battenhall’s Innovation team, which is focussed on new product development and continuous improvement of both external and internal products and services. We identify opportunities to solve problems and deliver greater value to both our internal teams and our customers. This means that sometimes we work on small, discrete projects that go from conception to deployment within a month, and at other times we work on large scale SaaS products that have a lifespan of years.

The role of Python Developer will have a primary focus of accelerating the development of our flagship product, which hinges on getting data out of social platforms efficiently, storing it, wrangling it, and making it available to the front end. As such, experience as a back-end developer, a data engineer or a data pipeline specialist with experience in Python would also be considered.

This is an exciting time to join this growing team, with huge opportunities for personal growth and career development as an early team member.


Responsibilities:

Business logic and core systems:

  • Develop the underlying business logic and infrastructure that brings together the frontend customer journey, third party data and proprietary business logic to create a distinctive experience.
  • Develop an optimised API for our front end to make efficient calls to, involving wrangling data and ensuring it is available in the final parsed format for UI display.
  • Create custom data loaders to import and abstract third-party data into a universal and scalable system.


Data Pipelines:

  • Maintain, improve, and create data pipelines between social platforms’ APIs (Instagram, Facebook, LinkedIn, TikTok, X, YouTube, Threads) and our Postgres database.
  • Use tools such as Dagster, Fivetran, and Big Query to ensure efficient data flow and processing.


Database Management / Efficiency:

  • Enhance the performance of queries to the database.
  • Ensure data integrity and optimise database operations.


Data Processing

  • Provide better access to summarised data via RPC functions or similar approaches.
  • Implement efficient data wrangling processes to transform raw data into valuable insights.


Development of AI capabilities

  • Use of AI models to augment the core data systems and provide enhanced data for internal and external customers


Skills and qualifications:

  • Minimum of 4 years of experience in a similar role/s.
  • Proficiency in Python and SQL.
  • Familiarity with cloud infrastructure that enables rapid prototyping and publishing.
  • Experience with Python-based ETL tools (eg Dagster, Airflow), Postgres (hosted or via a DBaaS like Supabase), and cloud data (eg Big Query, Snowflake) is desirable.
  • Experience with NextJS and TypeScript would be considered ideal.
  • Strong communication and teamwork abilities to collaborate effectively with both technical and non-technical team members.
  • Enthusiasm for a startup-like environment, with a willingness to adapt and innovate.
  • Ability to work independently and manage time efficiently.
  • Experience in line management or team leading is a plus but not essential.


Contact us

If you believe you’re the right candidate, please get in touch with us at , including your CV, cover letter, and any relevant examples or a portfolio of work.

Battenhall has a commitment to diversity, equality, and inclusion within the workplace. Please be eligible to work within the UK.

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.

Tips for Staying Inspired: How Machine Learning Pros Fuel Creativity and Innovation

Machine learning (ML) continues to reshape industries—from personalised e-commerce recommendations and autonomous vehicles to advanced healthcare diagnostics and predictive maintenance in manufacturing. Yet behind every revolutionary model lies a challenging and sometimes repetitive process: data cleaning, hyperparameter tuning, infrastructure management, stakeholder communications, and constant performance monitoring. It’s no wonder many ML professionals can experience creative fatigue or get stuck in the daily grind. So, how do machine learning experts keep their spark alive and continually generate fresh ideas? Below, you’ll find ten actionable strategies that successful ML engineers, data scientists, and research scientists use to stay innovative and push boundaries. Whether you’re an experienced practitioner or just breaking into the field, these tips can help you fuel creativity and discover new angles for solving complex problems.

Top 10 Machine Learning Career Myths Debunked: Key Facts for Aspiring Professionals

Machine learning (ML) has become one of the hottest fields in technology—touching everything from recommendation engines and self-driving cars to language translation and healthcare diagnostics. The immense potential of ML, combined with attractive compensation packages and high-profile success stories, has spurred countless professionals and students to explore this career path. Yet, despite the boom in demand and innovation, machine learning is not exempt from myths and misconceptions. At MachineLearningJobs.co.uk, we’ve had front-row seats to the real-life career journeys and hiring needs in this field. We see, time and again, that outdated assumptions—like needing a PhD from a top university or that ML is purely about deep neural networks—can mislead new entrants and even deter seasoned professionals from making a successful transition. If you’re curious about a career in machine learning or looking to take your existing ML expertise to the next level, this article is for you. Below, we debunk 10 of the most persistent myths about machine learning careers and offer a clear-eyed view of the essential skills, opportunities, and realistic paths forward. By the end, you’ll be better equipped to make informed decisions about your future in this dynamic and rewarding domain.

Global vs. Local: Comparing the UK Machine Learning Job Market to International Landscapes

How to evaluate opportunities, salaries, and work culture in machine learning across the UK, the US, Europe, and Asia Machine learning (ML) has rapidly transcended the research labs of academia to become a foundational pillar of modern technology. From recommendation engines and autonomous vehicles to fraud detection and personalised healthcare, machine learning techniques are increasingly ubiquitous, transforming how organisations operate. This surge in applications has fuelled an extraordinary global demand for ML professionals—data scientists, ML engineers, research scientists, and more. In this article, we’ll examine how the UK machine learning job market compares to prominent international hubs, including the United States, Europe, and Asia. We’ll explore hiring trends, salary ranges, workplace cultures, and the nuances of remote and overseas roles. Whether you’re a fresh graduate aiming to break into the field, a software engineer with an ML specialisation, or a seasoned professional seeking your next challenge, understanding the global ML landscape is essential for making an informed career move. By the end of this overview, you’ll be equipped with insights into which regions offer the best blend of salaries, work-life balance, and cutting-edge projects—plus practical tips on how to succeed in a domain that’s constantly evolving. Let’s dive in.