National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Engineer

Gismart
London
2 days ago
Applications closed

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Social network you want to login/join with:
Gismart is a value-driven mobile app developer with a strong presence in the Health & Wellness, Utilities, and Music app markets. We have recently achieved a milestone of over 1 billion downloads worldwide, aligning with our mission to promote well-being globally. Headquartered in London, UK, Gismart is a dynamic international company with a diverse team of over 250 professionals from various backgrounds in entertainment, music, and technology, committed to innovation and growth.
Our mission:
Become a stepping stone in our customers’ journeys of self-improvement.
Our values:
Growth:

Embrace curiosity, continuous learning, and development.
Impact:

Strive to be a positive force and give back to the community.
Trust:

Build trust through consistent actions and integrity.
Honesty:

Be courageous in facing the truth.
Balance:

Recognize that work-life balance is essential for fulfillment.
If you are passionate about mobile app development and want to join a company that’s reshaping the industry, Gismart offers exciting career opportunities, a supportive culture, and meaningful impact.
What you will do:
Design, develop, and maintain data pipelines and ETL processes for our internal Data Warehouse (DWH).
Develop and support integrations with third-party systems.
Ensure the quality of data presented in Business Intelligence (BI) dashboards.
Collaborate with data engineers, analysts, and scientists to troubleshoot data issues and optimize workflows.
Key Qualifications:
At least 2 years of experience in BI/DWH development.
Strong knowledge of database concepts and SQL.
Experience designing, implementing, and maintaining ETL pipelines.
Proficiency in writing production-level Python code.
Experience with cloud technologies (AWS, Azure, GCP).
Bachelor’s or Master’s degree in Computer Science, Mathematics, or related field.
Experience with Apache Airflow, Kafka, Amazon Redshift.
Experience with BI tools like Tableau or Power BI.
Knowledge of billing systems, financial reporting, and subscription monetization.
Support for product and marketing data analytics.
Employee Benefits:
Remote-First Culture:

Flexible work arrangements worldwide, remote or in hubs.
Relocation Program:

Assistance for relocating to Poland, including legal and accounting support.
Coworking Compensation:

50% coverage for coworking spaces globally.
Flexible Public Holidays:

6 fixed holidays plus 5 additional days of your choice.
Full Sick Leave Compensation.
Health Support:

Medical insurance, coverage for sports and therapy costs.
Personal Equipment:

Provision or maintenance support for your tools.
Learning & Development:

Coverage for courses (70%) and language training (80%).
Time Off:

18 vacation days, 3 personal days, plus additional days per tenure.
Corporate Events:

In-person meetups and team-building activities across hubs.

#J-18808-Ljbffr

National AI Awards 2025

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.

How to Present Machine Learning Solutions to Non-Technical Audiences: A Public Speaking Guide for Job Seekers

Machine learning is driving change across nearly every industry—from retail and finance to health and logistics. But while the technology continues to evolve rapidly, the ability to communicate it clearly has become just as important as building the models themselves. Whether you're applying for a junior ML engineer role, a research position, or a client-facing AI consultant job, UK employers increasingly expect candidates to explain complex machine learning solutions to non-technical audiences. In this guide, you’ll learn how to confidently present your work, structure your message, use simple visuals, and explain the real-world value of machine learning in a way that makes sense to people without a background in data science.

Machine Learning Jobs UK 2025: 50 Companies Hiring Now

Bookmark this page—we refresh the Hotlist every quarter so you always know who’s really scaling their ML teams. The UK’s National AI Strategy, a £2 billion GenAI accelerator fund and a record flow of private capital have kicked ML hiring into overdrive for 2025. Whether you build production‑grade LLM services or optimise on‑device models for edge hardware, employers need your skills now. Below you’ll find 50 organisations that advertised UK‑based machine‑learning vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the type of employer—and mission—that excites you. For each company we list: Main UK hub Example live or recent vacancy Why it’s worth a look (stack, impact, culture) Search any employer on MachineLearningJobs.co.uk to see real‑time adverts, or set a free alert so fresh openings drop straight in your inbox.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.