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For Companies At a Glance
- Tasks: Join our team to design and optimize data pipelines using cutting-edge technologies.
- Company: Be part of a forward-thinking company focused on finance analytics technology.
- Benefits: Enjoy a hybrid work model with three days in the office and collaborative team culture.
- Why this job: Contribute to impactful data initiatives while working with innovative tools and a supportive team.
- Qualifications: Expertise in Snowflake, Python, and cloud technologies is essential; finance knowledge is a plus.
- Other info: This role offers a chance to grow in a dynamic environment with agile methodologies.
The predicted salary is between 36000 - 60000 £ per year.
Data Engineer – Finance Analytics Technology
We are looking for a dedicated Data Engineer to join the Finance Analytics Technology team. In this role, you’ll play a key part in building, maintaining, and optimising a modern data ecosystem. This permanent opportunity involves working with leading technologies, including Snowflake, Python, Informatica, and Azure, to deliver high-quality data solutions that support business-critical decision-making.
With a hybrid working model and three days a week in the office, this role provides the chance to collaborate closely with cross-functional teams in a dynamic and supportive environment.]
Key Responsibilities:
- Design, build, and optimise scalable data pipelines using ETL and ELT methodologies.
- Utilise Snowflake for efficient data storage, processing, and analytics.
- Automate data processes and integrate data from multiple sources using Python and SQL.
- Leverage Azure cloud-native technologies to enhance data infrastructure, ensuring scalability, performance, and security.
- Collaborate with data analysts, BI developers, and enterprise data teams to align solutions with business requirements and maintain data governance standards.
- Apply domain knowledge in finance-related data to improve accuracy, enhance models, and meet business needs.
- Stay informed about developments in cloud and data technologies, contributing to the organisation’s data strategy.
- Participate fully in the agile development lifecycle, including sprint planning, design reviews, and delivering data tasks within two-week cycles.
- Ensure compliance with existing standards while contributing to the refinement of best practices in cloud data engineering.
Essential Skills
- Expertise in building data pipelines and architectures with Snowflake, Python, and Informatica.
- Familiarity with Azure and other cloud-native technologies.
- Strong understanding of finance-related data domains and their application in data engineering.
- Problem-solving ability, combined with excellent collaboration and communication skills, to work effectively with technical and non-technical teams.
- Experience working within modern technology stacks and agile methodologies.
- Background in collaborating with geographically distributed development teams.
Desirable Skills
- Knowledge of reporting tools such as Power BI.
- Familiarity with SAP FI datasets or platforms like SAP BW, SAP Analysis, and Business Objects.
This is an exciting opportunity to contribute to meaningful data-driven initiatives, working with a forward-thinking team on innovative projects. If this sounds like your next step, we’d love to hear from you!
Qh4 Consulting | Finance Data Engineer employer: Qh4 Consulting
Contact Detail:
Qh4 Consulting Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Qh4 Consulting | Finance Data Engineer
✨Tip Number 1
Familiarize yourself with the specific technologies mentioned in the job description, such as Snowflake, Python, and Azure. Consider building a small project or contributing to open-source projects that utilize these tools to demonstrate your hands-on experience.
✨Tip Number 2
Network with professionals in the finance data engineering field. Attend industry meetups or webinars focused on data analytics and cloud technologies. This can help you gain insights into the role and potentially connect you with someone at StudySmarter.
✨Tip Number 3
Stay updated on the latest trends in data engineering and finance analytics. Follow relevant blogs, podcasts, or online courses to enhance your knowledge and show your passion for the field during interviews.
✨Tip Number 4
Prepare to discuss your problem-solving skills and how you've collaborated with cross-functional teams in past projects. Be ready to provide examples that highlight your ability to work effectively in an agile environment, as this is crucial for the role.
We think you need these skills to ace Qh4 Consulting | Finance Data Engineer
Some tips for your application 🫡
Understand the Role: Take the time to thoroughly read the job description. Understand the key responsibilities and essential skills required for the Data Engineer position, especially focusing on technologies like Snowflake, Python, and Azure.
Tailor Your CV: Customize your CV to highlight relevant experience and skills that align with the job requirements. Emphasize your expertise in building data pipelines, working with finance-related data, and familiarity with cloud technologies.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of finance analytics. Mention specific projects or experiences that demonstrate your problem-solving abilities and collaboration skills.
Highlight Agile Experience: If you have experience working in agile environments, make sure to mention it. Discuss how you've contributed to sprint planning or collaborated with cross-functional teams, as this is a key aspect of the role.
How to prepare for a job interview at Qh4 Consulting
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Snowflake, Python, and Informatica in detail. Highlight specific projects where you built data pipelines or optimized data processes, as this will demonstrate your hands-on expertise.
✨Understand the Finance Domain
Since the role involves finance-related data, brush up on key concepts in finance analytics. Be ready to explain how your knowledge can enhance data accuracy and support business decision-making.
✨Emphasize Collaboration Experience
This position requires working closely with cross-functional teams. Share examples of how you've successfully collaborated with both technical and non-technical stakeholders, especially in agile environments.
✨Stay Updated on Technology Trends
Demonstrate your commitment to continuous learning by discussing recent developments in cloud and data technologies. Mention any relevant courses or certifications you've completed to show your proactive approach.
