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For Companies At a Glance
- Tasks: Analyse data products and collaborate with teams to create robust solutions.
- Company: Join a pioneering company delivering data-driven insights to top brands globally.
- Benefits: Enjoy a hybrid work model, cutting-edge technologies, and opportunities for continuous learning.
- Why this job: Tackle exciting data challenges in a fast-paced environment while making a real impact.
- Qualifications: Experience in SQL and Python, preferably with AWS; strong analytical and problem-solving skills required.
- Other info: Be part of a collaborative team that values innovation and knowledge sharing.
The predicted salary is between 36000 - 60000 £ per year.
My client has been a pioneer in delivering data-driven insights to the media and market research industries for over a decade. Their platform provides unique and actionable data solutions to top brands and partners worldwide, empowering them to make informed, strategic decisions.
They are seeking an experienced Data Engineer to work closely with our Machine Learning and Product teams to ensure our data products are of the highest quality. The ideal candidate will have strong analytical skills, expertise in Python and SQL, and a passion for debugging and improving data processes. This role requires collaborative problem-solving, a keen attention to detail, and the ability to translate complex business requirements into robust data solutions.
The Role:
Your primary responsibilities will involve analysing and troubleshooting issues with data products and collaborating with both Product and ML teams to devise robust solutions. You will apply strong Python and SQL skills to ensure data accuracy, integrity, and scalability, while also engaging in continuous improvements to our data products. You will tackle complex data challenges in a fast-paced, exciting environment, leveraging cutting-edge Big Data open-source technologies like Apache Spark, as well as Amazon Web Services (AWS) solutions such as Elastic MapReduce (EMR), Athena, and Lambda to develop innovative and scalable data solutions.
Key Responsibilities:
- Continually review and measure the performance of data products and drive innovation and improvements.
- Become a subject matter expert for data products and supporting processes and be able to present to others to knowledge share.
- Regularly reviewing colleagues’ work and providing helpful feedback.
- Working with stakeholders to fully understand requirements and be a technical reference point for product team members on customer calls.
- Writing application code and tests that conform to standards.
- Adhering to Company Policies and Procedures with respect to Security, Quality and Health & Safety.
About You:
Here’s what we’re looking for:
- SQL and Python development experience as a Data Engineer, preferably using AWS or equivalent cloud provider.
- Analytical skills to be able to present decisions to stakeholders in a data driven way.
- The ability to problem-solve and break down complex problems, whilst working on complex datasets.
- Knowledge of agile software development best practices including continuous integration, automated testing and working with software engineering requirements and specifications.
- Good interpersonal skills, positive attitude and willing to help other members of the team.
Data Engineer - Machine Learning - Hybrid / Python - SQL - Manchester employer: The Workplace Consultancy
Contact Detail:
The Workplace Consultancy Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Machine Learning - Hybrid / Python - SQL - Manchester
✨Tip Number 1
Familiarise yourself with the specific technologies mentioned in the job description, such as Apache Spark and AWS services like EMR and Lambda. Having hands-on experience or projects showcasing these skills can set you apart during discussions.
✨Tip Number 2
Engage with the data engineering community online, particularly around Python and SQL. Participating in forums or contributing to open-source projects can help you build a network and gain insights that may be beneficial during your interview.
✨Tip Number 3
Prepare to discuss real-world examples of how you've solved complex data problems in previous roles. Being able to articulate your thought process and the impact of your solutions will demonstrate your analytical skills effectively.
✨Tip Number 4
Showcase your collaborative skills by preparing to discuss how you've worked with cross-functional teams in the past. Highlighting your ability to communicate technical concepts to non-technical stakeholders can be a key advantage.
We think you need these skills to ace Data Engineer - Machine Learning - Hybrid / Python - SQL - Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and any relevant cloud technologies like AWS. Emphasise your analytical skills and any previous work with data products to align with the job requirements.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and problem-solving. Mention specific projects where you've successfully debugged or improved data processes, showcasing your collaborative skills with teams.
Showcase Relevant Projects: If you have worked on projects involving Big Data technologies or machine learning, include these in your application. Describe your role, the challenges faced, and how you contributed to the success of the project.
Prepare for Technical Questions: Anticipate technical questions related to SQL, Python, and data engineering practices. Be ready to discuss your approach to troubleshooting data issues and how you ensure data accuracy and integrity in your work.
How to prepare for a job interview at The Workplace Consultancy
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and SQL in detail. Bring examples of past projects where you successfully implemented data solutions, especially those involving AWS technologies like EMR or Lambda.
✨Demonstrate Problem-Solving Abilities
Expect to face technical challenges during the interview. Practice explaining your thought process when troubleshooting data issues, and be ready to break down complex problems into manageable parts.
✨Engage with Collaborative Scenarios
Since the role involves working closely with Product and Machine Learning teams, prepare to discuss how you've collaborated in the past. Highlight any experiences where you provided feedback or worked with stakeholders to understand requirements.
✨Emphasise Continuous Improvement Mindset
Talk about your approach to reviewing and improving data products. Share specific instances where you identified areas for enhancement and how you implemented changes to drive innovation.
