At a Glance
- Tasks: Build and maintain data pipelines, dashboards, and cloud infrastructure.
- Company: Join Mercer, a leader in data solutions with a vibrant culture.
- Benefits: Professional development, inclusive environment, and diverse career opportunities.
- Other info: Dynamic workplace with a focus on innovation and teamwork.
- Why this job: Make an impact with cutting-edge data technologies and collaborative teams.
- Qualifications: Bachelor's degree and 3-5 years in data engineering; SQL and Python skills required.
The predicted salary is between 50000 - 65000 £ per year.
Mercer is seeking candidates for the following position based in the London office: Data Engineer.
What can you expect? As a Data Engineer, you will be responsible for supporting the design, development, and maintenance of our data pipelines, data products, and infrastructure. You will work closely with senior team members to ensure data is collected, stored, and processed efficiently to meet the needs of our business teams. This role offers an excellent opportunity to grow your technical skills and gain valuable experience in a fast-paced environment.
Key Responsibilities
- Data Pipeline Development: Assist in building and maintaining ETL (Extract, Transform, Load) processes to integrate data from various sources into our Data Lakehouse.
- Data Visualisation: Develop and maintain dashboards and reports using Power BI, providing actionable insights to stakeholders.
- Cloud Services: Support the setup and maintenance of AWS cloud infrastructure, including solutions such as S3, Glue, Lambda, Step Functions.
- Data Quality & Deployment: Monitor and ensure the accuracy, completeness, and reliability of data products through validation using data build tool (dbt).
- Version Control: Knowledge of version control systems, particularly Git, for managing codebase and collaborating with other team members.
- Collaboration: Work closely with data analysts, data scientists, and other cross-functional teams to understand data requirements and deliver optimal solutions.
- Documentation: Create and maintain technical documentation for data workflows, processes, and systems.
- SQL: Demonstrated ability to write complex SQL queries for data extraction, manipulation, and transformation.
- Python: Experience with Python programming for data manipulation, analysis, and automation. Understanding of Python's best practices, including code readability, modularity, and documentation.
What you need to have
- Education: Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
- Experience: 3-5 years of experience in data engineering or a related field.
- Technical Skills: Proficiency in SQL for data manipulation and querying. Experience with Power BI for data visualisation and dashboard creation. Experience with Python for data processing and scripting. Familiarity with AWS services, such as S3, Glue, Lambda, Step Functions, LakeFormation, CloudWatch and IAM.
- Soft Skills: Excellent problem-solving abilities and attention to detail. Strong communication and interpersonal skills. Ability to work effectively in a team and independently.
What makes you stand out
- Experience with data warehousing concepts and technologies.
- Knowledge of other BI tools (e.g., Tableau, Looker) and data modelling techniques.
- Familiarity with big data technologies (e.g., Hadoop, Spark).
- Familiarity with modern data architecture (e.g., Data Mesh, Fabric).
- An understanding of infrastructure as code (e.g., Terraform).
- Experience with CI/CD pipelines and version control systems like Git.
- Familiarity with Dremio and/or Databricks as a data lake engine.
Why join our team
We help you be your best through professional development opportunities, interesting work and supportive leaders. We foster a vibrant and inclusive culture where you can work with talented colleagues to create new solutions and have impact for colleagues, clients and communities. Our scale enables us to provide a range of career opportunities, as well as benefits and rewards to enhance your well-being.
Equal Opportunity Employer
Marsh is committed to embracing a diverse, inclusive and flexible work environment. We aim to attract and retain the best people and embrace diversity of age background, civil partnership status, disability, ethnic origin, family duties, gender orientation or expression, gender reassignment, marital status, nationality, parental status, personal or social status, political affiliation, race, religion and beliefs, sex/gender, sexual orientation or expression, skin color, or any other characteristic protected by applicable law. We are an equal opportunities employer. We are committed to providing reasonable adjustments in accordance with applicable law to any candidate with a disability to allow them to fully participate in the recruitment process. If you have a disability that may require reasonable adjustments, please contact us at reasonableaccommodations@marsh.com.
Data Engineer employer: Marsh
Mercer is an exceptional employer that prioritises professional development and fosters a vibrant, inclusive culture in its London office. As a Data Engineer, you will have the opportunity to work with talented colleagues on innovative projects while benefiting from a range of career growth opportunities and comprehensive rewards that enhance your well-being.
StudySmarter Expert Advice🤫
We think this is how you could land Data 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 Marsh!
✨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 Data Engineer at Marsh.
✨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 Marsh.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer at Marsh, 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 Data Engineer
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 Marsh, 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 Marsh. 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 Marsh
✨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 Marsh!
✨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.
