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: Enjoy remote work flexibility and competitive pay rates.
- Why this job: Be part of a dynamic team making impactful data-driven decisions.
- Qualifications: 5+ years in SQL and Python, strong analytical skills required.
- Other info: Open for a limited time; 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.
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 decisions, as this aligns closely with the responsibilities of the role.
✨Tip Number 4
Stay updated on the latest trends in data engineering and analytics. Being knowledgeable about current best practices and emerging technologies will not only help you in interviews but also demonstrate your commitment to continuous learning.
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 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 or customer satisfaction.
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. Highlight specific projects where you've built or optimised data pipelines, and be ready to explain the technical challenges you faced and how you overcame them.
✨Demonstrate Analytical Thinking
Since the role requires an analytical mindset, come equipped with examples of how you've derived insights from complex datasets. Discuss any metrics or dashboards you've developed and how they impacted decision-making within your team.
✨Emphasise Collaboration
This position involves working cross-functionally, so be sure to share experiences where you've collaborated with engineers, product managers, or data scientists. Highlight your ability to communicate technical concepts to non-technical stakeholders.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-world scenarios. Think about past situations where you had to support ad hoc data requests or troubleshoot issues, and be ready to walk through your thought process during those times.
