Senior Data Engineer

RVU Co UK
Hart District
2 weeks ago
Create job alert

Senior Data Engineer

Department:Data & Analytics

Employment Type:Full Time

Location:Fleet


Description

Hybrid with 2 days per week in our Fleet HQ, or 1 day Fleet and 1 day RVU London HQ (Tower Bridge) per week if more convenient.

Tempcoveris at the forefront of the fast-growing world of short term insurance. Our mission is to make car insurance flexible, quick, and easy for drivers. We’ve sold millions of policies that have helped drivers get where they need to go, but we’re not finished there. We’re growing our team to help us continue in that mission. If you are extraordinary at what you do and want to be a part of a rapidly growing business at the cutting edge of the InsureTech industry, we would love to hear from you.

The team/role

The Data and Analytics team within Tempcover provide a vital role in bringing data, MI and Insight to life for internal & external stakeholders and partners.

The Senior Data Engineer will be responsible for the design, build and maintenance of the cloud based data platform, supporting the wider business in making data-driven decisions. Leading the development and optimisation of data pipelines, data models and data quality controls, this role will require collaboration with data analysts and business stakeholders to translate data needs into scalable and reliable solutions.

Over the past 4 years, the data platform has continually evolved through the expansion of data models, integrations and underpinning technologies. This evolution is set to continue at pace as we refine our data ingestion solutions and expand our insight capability across the business.


What you'll be doing

Key Duties & Responsibilities:

  • Design, develop, and maintain robust data pipelines and ETL processes
  • Create and manage accurate and performant data models to support Tempcover’s analytical capability.
  • Propose and implement internal improvement initiatives to the data platform.
  • Lead proactive approach to performance monitoring/tuning.
  • Leverage cloud-based platforms to build a scalable data infrastructure.
  • Provide continued support to ensure high availability of data to the wider business
  • Work closely with analysts across MI, Marketing, Product and Pricing to understand data requirements and translate them into effective solutions.
  • Work with rigour to ensure data quality/accuracy.
  • Mentor and guide junior data engineers, providing technical expertise and project oversight.


What we're looking for

  • Advanced proficiency in SQL databases, including writing complex queries, indexing and query optimisation.
  • Experience of ETL tools such as Azure Data Factory, Google Cloud Dataflow, FiveTran, Databricks.
  • Solid understanding of data warehousing techniques; ETL/ELT processes and dimensional modelling.
  • In-depth knowledge of cloud-based data infrastructure (Azure, AWS, GCP).
  • Excellent problem-solving skills and the ability to work independently and collaboratively in a fast-paced environment.
  • Proficiency with Git/DevOps for version control and collaboration.

Beneficial:

  • API integration.
  • Knowledge of Python is beneficial.
  • Ability to work within a SCRUM agile development environment.
  • Understanding of visualisation and dashboard products (e.g. Power BI, Tableau, Qlik)


Benefits

We want to give you a great work environment, support your growth both personally and professionally, and provide benefits that make your time at RVU even more enjoyable. Here are some of the benefits you can look forward to:

  • 10% discretionary yearly bonus and yearly pay reviews (based on RVU and personal performance)
  • A hybrid working approach with 2 in-office days per week and up to 22 working days per year to “work from anywhere”
  • Employer matching pension contributions up to 7.5%
  • A one-off £300 “Work from Home” budget to help contribute towards a great work environment at home
  • Excellent maternity, paternity, shared parental and adoption leave policy, for those key moments in your life
  • 25 days holiday (increasing with years of employment to 30 days) + 2 days “My Time” per year
  • Private medical cover, critical illness cover and employee assistance programme
  • A healthy learning and training budget
  • Electric vehicle and cycle to work schemes
  • Regular events - from team socials to company-wide events with insightful external speakers, we want to make sure our colleagues continue to feel connected

#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer - Fabric - £70,000 - London

Senior Data Engineer - Remote - £70k

Senior Data Engineer - DV Cleared

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 Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.