Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and maintain data pipelines to enhance customer experience.
- Company: Join the largest social media company with over 2 billion users.
- Benefits: Remote work, competitive pay, and potential for extension.
- Why this job: Make a real impact in a dynamic tech environment while collaborating with diverse teams.
- Qualifications: 5+ years in SQL and Python; strong analytical skills required.
- Other info: Open to all applicants; inclusivity is a priority.
An exciting opportunity has arisen for an experienced Data Engineer to join a central support function within a high-impact technology organisation. This role focuses on enhancing customer experience and satisfaction through advanced data solutions in a dynamic support environment.
You will be responsible for designing and maintaining scalable data pipelines and developing metrics that empower teams to make data-informed decisions. The ideal candidate will have strong analytical skills, a hands-on approach to solving complex data challenges, and the ability to work cross-functionally with engineers, product managers, and data scientists.
Key Responsibilities:- Build, maintain, and optimise data pipelines and architectures.
- Develop success metrics and dashboards to track team performance.
- Translate business needs into technical solutions using SQL and Python.
- Support ongoing and ad hoc data requests, including bug fixes and deep dives.
- Collaborate with cross-functional teams to ensure data quality and logging accuracy.
- Contribute to the improvement of knowledge management systems through better data measurement and insights.
- 5+ years of experience in SQL and Python development.
- Strong background in data modelling, analytics, and visualisation (e.g. Tableau, MicroStrategy).
- Proven experience with integration tools such as Azure Data Factory and Apache Airflow.
- Ability to work independently while engaging with stakeholders across functions.
- Familiarity with business intelligence processes and experimentation data.
- Exposure to knowledge management or customer support data systems.
- Experience in fast-paced sectors such as tech, retail, or social media.
- Analytical mindset with the ability to derive meaningful insights from complex datasets.
Aquent is dedicated to improving inclusivity & is proudly an equal opportunities employer. We encourage applications from under-represented groups & are committed to providing support to applicants with disabilities. We aim to provide reasonable accommodation for any part of the employment process, to those with a medical condition, disability or neurodivergence.
Data Engineer employer: Aquent
Contact Detail:
Aquent 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 Data Factory and Apache Airflow. Having hands-on experience or even a project to showcase your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who work in tech or social media sectors. Engaging with them on platforms like LinkedIn can provide insights into the company culture and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your previous projects that involved building and optimising data pipelines. Be ready to explain your thought process and the impact of your work on business outcomes, as this will demonstrate your analytical mindset.
✨Tip Number 4
Showcase your ability to collaborate cross-functionally by preparing examples of how you've worked with product managers or data scientists in the past. This will highlight your teamwork skills, which are crucial for this role.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with SQL, Python, and data modelling. Emphasise any relevant projects or roles that demonstrate your ability to build and maintain data pipelines.
Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about data engineering and how your skills align with the responsibilities outlined in the job description. Mention your experience with tools like Azure Data Factory and Apache Airflow.
Showcase Analytical Skills: Provide specific examples of how you've used data to drive decisions in previous roles. Highlight any success metrics or dashboards you've developed that improved team performance.
Proofread Your Application: Before submitting, carefully proofread your application for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial for a Data Engineer role.
How to prepare for a job interview at Aquent
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL and Python in detail. Bring examples of projects where you've built or optimised data pipelines, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Analytical Thinking
Highlight your analytical mindset by discussing how you've derived insights from complex datasets. Prepare to share specific metrics or dashboards you've developed that had a significant impact on decision-making.
✨Emphasise Collaboration
Since this role involves working cross-functionally, be ready to talk about your experience collaborating with engineers, product managers, and data scientists. Share examples of how you ensured data quality and logging accuracy in team projects.
✨Understand the Company’s Mission
Research the client’s mission and values, especially their focus on customer experience and inclusivity. Be prepared to discuss how your skills and experiences align with their goals and how you can contribute to enhancing customer satisfaction.
