Senior Data Analytics Engineer

Senior Data Analytics Engineer

Full-Time 54000 - 66000 £ / year (est.) On-site
M

At a Glance

  • Tasks: Design and maintain data products using Azure Databricks, transforming data for business insights.
  • Company: Join Munich Re, a leader in insurance innovation with a focus on collaboration.
  • Benefits: Competitive salary, inclusive culture, and opportunities for professional growth.
  • Other info: Work in a diverse team that values inclusion and celebrates unique perspectives.
  • Why this job: Make a real impact by leveraging data to drive business decisions in a dynamic environment.
  • Qualifications: Experience in data engineering, advanced SQL skills, and familiarity with Power BI.

The predicted salary is between 54000 - 66000 £ per year.

London, England, United Kingdom

Company: Munich Re

Together, we engage with everything we have and are, to help humankind act braver and better.

About Great Lakes Insurance SE:

As a specialty provider of primary insurance services in the UK, Great Lakes London Branch ("GLLB") is a substantial part of Great Lakes Insurance SE in Munich. Our interlocked business model is to seize opportunities closely connected to the reinsurance core business and innovation opportunities, in our role as an integral part of the Munich Re Group.

This role sits within the Great Lakes Data & BI team, responsible for building and maintaining data products within the Azure Databricks lakehouse, including Silver and Gold table transformations and semantic layer outputs, and for diagnosing and resolving data issues arising from the data intake platform. Reporting to the Data & BI Lead, the successful candidate will work closely with IT on data modelling for Silver and Gold, bringing strong technical input to those discussions, while collaborating with the wider business, from Underwriters to Actuaries.

  • Design, build, and maintain Silver and Gold table transformations within the Azure Databricks lakehouse, in line with agreed medallion architecture principles.
  • Contribute technical input into data modelling discussions for Silver and Gold layers, working closely with IT to ensure models are performant and aligned to Munich Re modelling standards.
  • Investigate and resolve data quality issues arising from the data intake platform, working with the Platform team where root cause sits upstream.
  • Build new data products for business consumption, including outputs surfaced through various visualisation mediums (experience with Databricks Dashboards & Power BI preferred).
  • Collaborate with the Data & BI team, business stakeholders, and IT to translate technical requirements into robust, well-modelled data products.
  • Partner with business users to develop data products within the lakehouse, ensuring transformations are built for performance and reusability.
  • Support code and modelling reviews, helping to build shared confidence between the business data team and IT on business-owned data products.
  • Build and maintain Power BI reporting and dashboards where required to support business and data team needs.
  • Explain technical concepts and trade-offs clearly to non-technical stakeholders, including underwriters, actuaries, and other business users.
  • Work collaboratively across team boundaries, including with IT and the Platform team, and across the wider organisation.

Competencies:

  • Drives results (we think big) – you consistently achieve results even under tough circumstances, with the organisation's performance in the front of your mind.
  • Collaboration (we lead the 'we') – you identify opportunities and bring the right people together to work on a common goal, encouraging diversity of opinion, whilst maintaining clarity and unity of direction.
  • Persuades (we are clear and authentic) – you use clear and compelling arguments to gain the support, enthusiasm and commitment of others, whilst ensuring you take time to actively listen to the diversity of views and opinions.

Key Skills & Experience:

  • Proven experience in a Data Engineering role within the insurance industry.
  • Advanced SQL and PySpark skills, with hands-on experience building data transformations and data products.
  • Demonstrable data modelling experience, including practical experience with medallion architecture, and comfortable contributing technical input into modelling discussions alongside IT.
  • Experience with Databricks, including Delta Lake; familiarity with Unity Catalog and semantic layer/consumption-layer tooling is a plus (Power BI & Databricks Dashboards).
  • Power BI experience, able to build and maintain dashboards and reports where needed.
  • Proven ability to navigate challenging situations and stakeholders, balancing technical constraints against business urgency.
  • Strong communicator, able to explain technical work and trade-offs clearly to a non-technical audience.
  • Self-starter, comfortable working across all parts of the business - from Underwriters to Actuaries.
  • Experience working in an Agile/Scrum delivery environment, contributing to backlog refinement and sprint ceremonies.
  • Understanding of data governance principles and version-controlled development workflows.
  • Strong collaborator, able to work effectively within a close-knit team as well as across team boundaries, including with IT and the Platform team.
  • Understanding of LLMs, AI, and RAG within the insurance industry (experience with Databricks Genie advantageous).

Desired Qualifications and Educational Background:

  • Bachelor's degree in a scientific, mathematical, technical, or business discipline and/or relevant professional/technical qualifications (Databricks Certified Data Engineer, Azure Data Engineer Associate).
  • Sustained good performance in a data engineering role.
  • Experience within the insurance industry, ideally with exposure to Delegated Authority and/or Large Single Risk/Specialty business.
  • Familiarity with dimensional modelling concepts (star schemas, slowly changing dimensions) as applied within a modern lakehouse environment.

Thought Leaders:

You are seen as an expert in your field and will be the 'go to' person for your area of specialism within Munich Re.

Regulatory & Conduct Requirements:

In addition to the responsibilities set out above, the Senior Data Engineer role will also become responsible for ensuring compliance with Munich Re's Code of Conduct and the FCA Conduct Rules.

Equal Opportunities:

At Munich Re, Diversity, Equity, and Inclusion foster innovation and resilience and enable us to act braver and better. We recognise diversity can be multi-dimensional, intersectional, and complex, so we want to build a diverse workforce that includes a wide range of racial, ethnic, sexual, and gender identities; life, school, and career experiences; and political, religious, and personal beliefs. Additionally, we are committed to building an equitable and inclusive work environment where this diversity is celebrated, valued, and has equitable opportunities to succeed.

You can request an adjustment by speaking to your Talent Acquisition contact.

Senior Data Analytics Engineer employer: Munich Re

Munich Re is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong emphasis on employee growth, we offer numerous opportunities for professional development and mentorship, ensuring that our team members thrive in their careers. Our commitment to cutting-edge technology and Agile practices not only enhances job satisfaction but also positions our employees at the forefront of the insurance industry.

M

Contact Details:

Munich Re Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Analytics Engineer

✨Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Munich Re!

✨Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Analytics Engineer at Munich Re.

✨Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Munich Re.

✨Apply Directly through Our Website

When you find a suitable opening like Senior Data Analytics Engineer at Munich Re, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Data Analytics Engineer

Communication Skills
SQL
Python
Problem-Solving Skills
Data Engineering
Automation
Data Pipeline Development

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!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Munich Re, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Munich Re. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Munich Re

✨Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

✨Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

✨Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Munich Re!

✨Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.