At a Glance
- Tasks: Create and manage data assets, ensuring quality and usability in a cloud environment.
- Company: Join a leading global company focused on innovative data solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Why this job: Make an impact by engineering data flows that drive business decisions.
- Qualifications: Experience in data engineering and strong problem-solving skills required.
- Other info: Collaborative environment with a focus on technical leadership and innovation.
The predicted salary is between 36000 - 60000 £ per year.
The role is responsible for creating and managing trusted and analytical Commercial and procurement data assets. You will be seen as the primary engineering contact for this area, with an expectation to provide expert advice and technical leadership for product squads utilizing data assets under your oversight; composed of product leaders, data scientists, data domain experts and front-end developers.
Key responsibilities:
- Data Engineering
- Engineer and orchestrate data flows & pipelines using high quality, easily deployable, repeatable and extensible codebases that ingest and integrate data from many disparate data sources in a cloud environment using a progressive tech stack.
- Responsible for ensuring the quality, freshness and usability of supply chain in trusted zone(s).
- Create readable manageable code with proper test and CI/CD, managing data transformation and troubleshooting data processing issues as required.
- Follow RC Data Engineering best practices and contribute to their reinforcement, as well as shared assets such as Data Libraries.
- Build simple data models to support efficient and accurate analytical insight creation.
- Reduce data preparation efforts for solution users to expedite their processes and reduce errors.
- Perform data pipeline migrations if necessary.
- Implement alerting and monitoring capabilities to ensure high platform reliability in compliance with Mars Cyber Security Standards and Privacy Policies.
- Ensure that required expertise from outside the squad (e.g. architecture, cybersecurity) is engaged as appropriate.
- Technical Leadership
- Provide a technical viewpoint for product squads using data in your oversight, ensuring proposed solutions are viable and utilize existing tools and processes.
- Seek to break complex/functional requirements down into simple/technically manageable elements, and with the help of others estimate the efforts required and any risks associated with development.
- Partner with the Product Manager and Data Domain Lead to onboard any new development resources, ensuring they adopt coding standards set by the organization.
- Data Management and Governance
- Practice Data Lifecycle Management through Global Metadata and Access Control Management.
- Ensure all data models and assets have Data Quality Management standards implemented.
- Partner with functions and divisions to ensure the RC data capabilities roadmap, operating model and governance principles are best serving the organization data strategy.
Global Data Engineer F/M/X employer: Mars
Contact Detail:
Mars Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Global Data Engineer F/M/X
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving cloud environments and data pipelines. We want to see your coding prowess and how you tackle real-world problems, so make it easy for recruiters to see what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. We recommend practising common data engineering scenarios and being ready to discuss your approach to problem-solving. Remember, confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are genuinely interested in joining our team. So, hit that apply button and let’s get started!
We think you need these skills to ace Global Data Engineer F/M/X
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Global Data Engineer role. Highlight your experience with data flows, pipelines, and any relevant tech stacks you've worked with. We want to see how your skills align with our needs!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our team. Be sure to mention any specific projects or achievements that showcase your expertise.
Showcase Your Technical Skills: In your application, don't forget to highlight your technical skills, especially around coding standards, data quality management, and CI/CD practices. We love seeing candidates who are not just experienced but also up-to-date with best practices!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Mars
✨Know Your Data Engineering Basics
Make sure you brush up on your data engineering fundamentals. Understand how to engineer and orchestrate data flows and pipelines, as well as the importance of writing clean, manageable code. Be ready to discuss your experience with cloud environments and any tech stacks you've worked with.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled data processing issues in the past. Highlight your troubleshooting skills and how you've implemented alerting and monitoring capabilities to ensure platform reliability. This will demonstrate your technical leadership and ability to manage complex requirements.
✨Familiarise Yourself with Best Practices
Research and understand the best practices in data engineering, especially those relevant to the company you're interviewing with. Be ready to discuss how you've contributed to or reinforced these practices in your previous roles, particularly around data quality management and lifecycle management.
✨Engage with the Team Dynamics
Since you'll be working closely with product leaders, data scientists, and developers, show that you can collaborate effectively. Prepare to discuss how you've partnered with cross-functional teams in the past and how you plan to onboard new resources while ensuring adherence to coding standards.