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For Companies At a Glance
- Tasks: Build data pipelines and develop predictive models to enhance operations.
- Company: Join a fast-growing tech-for-good company focused on sustainability and social impact.
- Benefits: Enjoy hybrid work options and the chance to shape your career path.
- Why this job: Be a foundational member of a team driving real change through AI and data.
- Qualifications: Strong SQL and Python skills, with experience in ETL tools and BI platforms.
- Other info: No sponsorship available; ideal for those passionate about tech and sustainability.
The predicted salary is between 43000 - 52000 £ per year.
Salary/Package: £50k-£60k
Company Sector: Techforgood (Sustainability)
WFH / Hybrid: 2 days a week on site (East London)
Bounce are excited to partner with a customer we helped secure a Lead Data Engineer earlier this year, he's now looking for his first hire to join him! Our customer (recently Series A funded) are a fast-growing business focused on sourcing, refurbishing, and reselling IT devices to create real social and environmental impact.
We're hiring a foundational member of the Data & AI team to build the early infrastructure powering smarter pricing, faster sales, and more efficient operations. You'll start by owning data pipelines, reporting, and validation systems and grow into developing predictive models, pricing engines, and decision automation tools.
What You’ll Do (First 3–6 Months)
- Build automated ETL pipelines (Bronze-Silver-Gold architecture)
- Develop dashboards and reporting in Looker or Power BI
- Ingest and clean data from internal (Odoo/PostgreSQL) and external (eBay APIs) sources
- Define data quality rules, set up monitoring/logging, and support architecture decisions
What You Bring
- Strong SQL & Python (PySpark); hands-on with GCP or AWS
- Experience with modern ETL tools (dbt, Airflow, Fivetran)
- BI experience (Looker, Power BI, Metabase); Git and basic CI/CD exposure
- Background in a quantitative field; AI/ML interest a plus
- Bonus: Experience in manufacturing/logistics environments
Growth Path
- Evolve into AI-focused work: ML models, LLM copilots, real-time analytics
- Choose your track — AI engineer, data analyst, or architect
Why Join
- Shape our data platform from day one
- Work directly with leadership and across teams
- Drive core business outcomes — not vanity projects
- Be part of a small team using AI for commercial and social impact
Contact Detail:
Bounce Digital Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer (Greater London)
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, like SQL, Python, and modern ETL tools such as dbt and Airflow. Having hands-on experience with these technologies will not only boost your confidence but also demonstrate your readiness to hit the ground running.
✨Tip Number 2
Network with professionals in the tech-for-good sector, especially those involved in data engineering. Attend relevant meetups or webinars to connect with potential colleagues and learn more about the industry, which can give you valuable insights and possibly a referral.
✨Tip Number 3
Showcase any projects or experiences that highlight your ability to build data pipelines and dashboards. If you have worked on similar projects, be prepared to discuss them in detail during interviews to illustrate your practical skills and problem-solving abilities.
✨Tip Number 4
Research the company’s mission and values, particularly their focus on sustainability and social impact. Tailoring your conversations and questions around how you can contribute to these goals will show your genuine interest in the role and alignment with their vision.
We think you need these skills to ace Data Engineer (Greater London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with SQL, Python, and ETL tools. Emphasise any projects or roles that demonstrate your ability to build data pipelines and work with BI tools like Looker or Power BI.
Craft a Compelling Cover Letter: In your cover letter, express your passion for sustainability and how your skills align with the company's mission. Mention specific experiences that showcase your technical abilities and your interest in AI and data-driven decision-making.
Showcase Relevant Projects: If you have worked on any relevant projects, either professionally or as part of your studies, include them in your application. Detail your role, the technologies used, and the impact of the project, especially if it relates to data pipelines or predictive modelling.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial for a Data Engineer role.
How to prepare for a job interview at Bounce Digital
✨Showcase Your Technical Skills
Make sure to highlight your strong SQL and Python skills during the interview. Be prepared to discuss specific projects where you've used these technologies, especially in relation to ETL pipelines and data processing.
✨Demonstrate Your Problem-Solving Abilities
Prepare to discuss how you've tackled challenges in previous roles, particularly in building data pipelines or working with BI tools like Looker or Power BI. Use examples that showcase your analytical thinking and ability to create efficient solutions.
✨Understand the Company’s Mission
Research the company's focus on sustainability and social impact. Be ready to explain how your values align with theirs and how you can contribute to their mission of creating real environmental change through data.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the technology stack they use, and the growth opportunities within the role. This shows your genuine interest in the position and helps you assess if it's the right fit for you.
