At a Glance
- Tasks: Own and optimise data pipelines, ensuring data quality and supporting analytics.
- Company: Join a leading fintech company revolutionising financial solutions globally.
- Benefits: Enjoy competitive pay, health benefits, remote work options, and free online training.
- Other info: Inclusive culture with excellent career growth opportunities.
- Why this job: Make a real impact on data integrity and strategic insights in a dynamic environment.
- Qualifications: Experience in Data Engineering, strong Python and SQL skills required.
Aquent, a trusted partner to leading organizations worldwide, is excited to collaborate with a prominent financial technology company on a critical engagement. This company is at the forefront of empowering individuals and businesses with innovative financial solutions, driven by a mission to revolutionize how people manage their money. Join a team where your expertise directly contributes to robust data integrity and strategic insights across vital international operations, ensuring seamless functionality and critical decision-making.
Are you a hands-on data professional ready to make an immediate and significant impact? We are seeking an experienced individual to step into a high-autonomy role, becoming the sole technical owner responsible for maintaining essential data pipelines, analytics infrastructure, and reporting systems. This is your chance to directly influence the reliability and accuracy of data that underpins strategic decisions and operational excellence across key global markets. You will be instrumental in safeguarding data quality, supporting vital reporting, and executing time-sensitive data requests, playing a pivotal role in the company’s continued success.
Key Responsibilities
- Data Pipeline Operations: Take ownership of data pipelines, proactively triaging, debugging, and resolving pipeline breaks, tracking gaps, and partner feed issues across diverse data sources.
- Data Quality Assurance: Monitor the health, input quality, and freshness of the cloud-based data warehouse to ensure downstream reporting is consistently accurate and reliable.
- Business Intelligence & Analytics Support: Maintain and optimize data modeling and reporting infrastructure within a leading business intelligence platform, providing essential support for partner monitoring, offer setups, and click-report fixes.
- Automation & Efficiency: Leverage modern AI tools and workflows to innovate and automate day-to-day engineering and operational tasks, enhancing efficiency and reducing manual effort.
- Regulatory & Compliance Data: Execute urgent data pulls for critical regulatory returns, privacy data requests, complaint tracking, and marketplace metrics, consistently meeting tight deadlines.
- Performance Monitoring: Monitor baseline revenue pipelines and partner feeds across specific global regions, providing early visibility into unexpected anomalies or tracking gaps to inform timely interventions.
- Documentation & Knowledge Transfer: Maintain comprehensive system documentation and operational procedures, ensuring a smooth and efficient handover at the close of the engagement.
Must-Have Qualifications
- Demonstrated experience in Data Engineering or Analytics Engineering, including running and maintaining production data pipelines and warehousing systems.
- Strong proficiency in Python and SQL for codebase maintenance, scripting, and pipeline troubleshooting.
- Hands-on experience with a cloud-based data warehouse and data warehouse architecture.
- Hands-on experience with a leading data visualization and reporting platform for data modeling and reporting infrastructure.
- Proven track record of managing operational “business as usual” (BAU) workflows independently with low supervision and high reliability against hard deadlines.
- Excellent written and verbal communication skills, with the ability to translate complex technical data issues for non-technical stakeholders.
Nice-to-Have Qualifications
- Experience using AI developer tools and agentic workflows to automate data engineering tasks.
- Background in Financial Services, FinTech, or Technology environments.
- Prior experience handling critical regulatory reporting, privacy data requests, or financial compliance returns.
- Track record of stepping into existing codebases and delivering against fixed timelines in a contract or consulting capacity.
Aquent Talent connects the best talent in marketing, creative, and design with the world’s biggest brands. Our eligible talent get access to amazing benefits like subsidized health, vision, and dental plans, paid sick leave, and retirement plans with a match. We also offer free online training through Aquent Gymnasium.
Aquent is an equal-opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We’re about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.
Data Engineer [AQ-13526] in London employer: Aquent UK
Aquent is an exceptional employer that prioritises employee welfare and operational excellence, offering a dynamic work environment where creativity and innovation thrive. With comprehensive benefits programs, including subsidised health plans and retirement matching, employees are supported in their personal and professional growth. The inclusive culture fosters collaboration and values diverse perspectives, making it an ideal place for those looking to make a meaningful impact in a multinational setting.
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We think this is how you could land Data Engineer [AQ-13526] in London
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We think you need these skills to ace Data Engineer [AQ-13526] in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
