At a Glance
- Tasks: Design and build data pipelines for analytics and customer products.
- Company: Join Kpler, a diverse and inclusive tech company.
- Benefits: Competitive salary, flexible work options, and growth opportunities.
- Other info: Mentorship and collaboration with talented engineers and data scientists.
- Why this job: Make an impact with cutting-edge technology in a dynamic environment.
- Qualifications: Experience in software development and data processing.
The predicted salary is between 60000 - 80000 £ per year.
Role Description - What you will work on
- Design, build, and evolve batch and streaming data pipelines that power refinery modeling, analytics, and customer-facing products.
- Own complex data ingestion, transformation, validation, and delivery workflows across multiple data sources.
- Drive improvements in pipeline reliability, scalability, and observability, including retries, backfills, data quality checks, and monitoring.
- Lead schema design, versioning, and evolution strategies to support stable, long-lived data contracts.
- Build and maintain backend components and APIs used to serve data to downstream systems and applications.
- Partner closely with data scientists, product managers, and other engineers to translate domain requirements into robust technical solutions.
- Continuously improve existing systems as data volume, complexity, and product expectations grow.
Responsibilities
- Deliver high-quality, well-tested, and maintainable code, setting a strong example for engineering best practices.
- Own significant parts of the data platform end-to-end, from ingestion to production delivery.
- Make architectural contributions to data processing, storage, and delivery patterns.
- Contribute to and improve CI/CD pipelines, automation, and operational tooling.
- Instrument services and pipelines with metrics, logs, and alerts, and help define operational standards.
- Play an active role in incident response, root-cause analysis, and long-term system improvements.
- Review code, mentor other engineers, and help reinforce shared coding and architectural standards across the team.
Nice to have
- Exposure to Kafka, Spark, or streaming architectures.
- Experience with Kubernetes.
- Familiarity with event-driven or microservices architectures.
- Exposure to analytical datastores (e.g. Elasticsearch).
- Full-stack awareness (e.g. ability to read, review, and provide feedback on frontend or API-layer pull requests, without being a primary frontend contributor).
- Prior experience working on data products in energy, commodities, or industrial domains.
Kpler is committed to providing a fair, inclusive and diverse work environment. We welcome people of different backgrounds, experiences, abilities and perspectives and are an equal opportunity employer. Don’t meet every single requirement? Research shows that women and people of colour are less likely than others to apply if they feel like they don’t match 100% of the job requirements. Don’t let the confidence gap stand in your way, we’d love to hear from you! We understand that experience comes in many different forms and are dedicated to adding new perspectives to the team.
Senior Backend Engineer in London employer: Kpler group
At Kpler, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Senior Backend Engineer, you will have the opportunity to work on cutting-edge data pipelines in a supportive environment that values diversity and inclusion, while also benefiting from continuous professional development and mentorship. Our commitment to employee growth, coupled with our focus on impactful projects in the energy sector, makes Kpler a rewarding place to advance your career.
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We think you need these skills to ace Senior Backend Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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