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For Companies At a Glance
- Tasks: Join our team to build data solutions and support business intelligence initiatives.
- Company: Be part of a market leader in an innovative industry focused on data-driven decision-making.
- Benefits: Enjoy a competitive salary, flexible work arrangements, and opportunities for professional growth.
- Why this job: Make a real impact by transforming data into actionable insights while collaborating with diverse teams.
- Qualifications: Experience in data engineering, database design, and coding with SQL or Python is essential.
- Other info: This role is based in Birmingham, requiring 4 days on-site each week.
The predicted salary is between 36000 - 48000 £ per year.
A fantastic opportunity has come up to work for a genuine market leader in an exciting and innovative industry. They plan to build a newly created BI and Data Engineering division to work alongside other Data and Analytics teams across the group.
For this role, they need someone to serve as a central resource from within their Strategy and Analytics department, also working with, but not exclusive to, the Commercial, Finance, and Operational business functions, to help advance the group's data infrastructure and support in transforming data into actionable insights and triggered events for Business Intelligence (BI) and Customer Relationship Management (CRM) system purposes. This role will be instrumental in leveraging data to ensure a fully integrated approach to data-driven decision-making and also business strategy.
Day-to-day tasks
- Work across the group and with the divisions' data partners to leverage all available data, building out the group's database, reporting and insights capabilities to enable data-led decision making.
- Design, develop and maintain scalable, user-friendly and automated systems, data solutions and reporting that will support our analytical and business needs.
- Support the insight team with visualisations, reporting and stakeholder engagement through monthly/quarterly/annual departmental reviews.
- Use data science/statistical modelling tools in collaboration with the analyst team and departmental stakeholders to develop Artificial Intelligence (AI) and Machine Learning (ML) functions and analytics.
- Create and manage a knowledge-base, including documentation of your designs (e.g., system design, functional design, data flow design) ensuring there is version control and contingency processes for all aspects.
Required skills and experience for the role
- Demonstrable experience or certification(s) within the field of data engineering, data science, and/or business analysis.
- Practical experience of database design and data transformation, supported by ETL processing.
- Managing data pipelines & orchestration that enable the transfer and processing of data (Databricks, Microsoft Fabric, Alteryx, Snowflake, Apache).
- Coding and programming, capable of working through complex problems with others from the team, adapting quickly to changing market trends and business needs (SQL, Python or R).
- Utilising cloud-based services and corresponding toolsets (Microsoft Azure, GCP, AWS or similar).
- Comfortable handling structured and unstructured data, from 1st, 2nd, and 3rd party data sources, combining multiple data sets to produce a cohesive picture of performance and derive insights and recommendations.
- Experience working directly with business stakeholders ensuring complex information is articulated in a meaningful way.
Applying for the opportunity
If you feel you have the required skills and experience and want to be considered for this opportunity, please forward an up-to-date version of your CV. If we feel your profile is a suitable match, someone will contact you within 48 hours.
Data Engineer employer: Digital Waffle
Contact Detail:
Digital Waffle Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, such as Azure, SQL, and Python. Having hands-on experience or projects that showcase your skills with these technologies can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who work with BI and analytics. Attend local meetups or online webinars to connect with industry experts and gain insights into the latest trends and best practices.
✨Tip Number 3
Prepare to discuss your experience with data pipelines and ETL processes during interviews. Be ready to share specific examples of how you've managed data transformation and orchestration in previous roles or projects.
✨Tip Number 4
Showcase your ability to communicate complex data insights to non-technical stakeholders. Practice explaining your past projects in a way that highlights your impact on business decisions, as this is crucial for the role.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, BI, and the specific tools mentioned in the job description, such as Azure, Python, and SQL. Use keywords from the job listing to ensure your application stands out.
Showcase Your Projects: Include examples of past projects where you designed or maintained data solutions, managed data pipelines, or worked with AI/ML functions. This will demonstrate your practical experience and problem-solving skills.
Highlight Collaboration Skills: Since the role involves working with various business functions, emphasise your experience in collaborating with stakeholders. Provide examples of how you've communicated complex data insights effectively.
Craft a Strong Cover Letter: Write a cover letter that not only summarises your qualifications but also expresses your enthusiasm for the role and the company. Mention why you're excited about contributing to their new BI and Data Engineering division.
How to prepare for a job interview at Digital Waffle
✨Showcase Your Technical Skills
Make sure to highlight your experience with Azure, Python, and SQL during the interview. Be prepared to discuss specific projects where you utilised these technologies, as this will demonstrate your practical knowledge and problem-solving abilities.
✨Understand the Business Context
Familiarise yourself with the company's industry and how data engineering plays a role in their business strategy. This will help you articulate how your skills can contribute to their goals, especially in transforming data into actionable insights.
✨Prepare for Scenario-Based Questions
Expect questions that assess your ability to handle real-world data challenges. Think of examples where you've designed scalable systems or managed data pipelines, and be ready to explain your thought process and the outcomes.
✨Engage with Stakeholders
Since the role involves working with various business functions, demonstrate your communication skills by discussing how you've previously engaged with stakeholders. Share examples of how you translated complex data into meaningful insights for non-technical audiences.
