At a Glance
- Tasks: Design and develop modern cloud-based data solutions in a collaborative Agile environment.
- Company: Join a leading investment management organisation with a focus on innovation.
- Benefits: Initial 4-month contract, hybrid working, and potential for extension.
- Other info: Collaborative team culture with opportunities for professional growth.
- Why this job: Work with cutting-edge Azure and Snowflake technologies to solve complex data challenges.
- Qualifications: Experience in cloud data engineering, especially with Snowflake and Python.
The predicted salary is between 50000 - 70000 £ per year.
Overview
Data Engineer — Contract: 4 Months Initial Contract (Likely Extension). Location: London (Hybrid Working). IR35 Status: Inside IR35.
The Opportunity
An exciting opportunity has arisen for an experienced Data Engineer to join the technology team of a leading investment management organisation. Working within a highly collaborative Agile environment, you'\'ll play a key role in designing, developing and enhancing modern cloud-based data solutions that support front-office investment teams and critical business functions. This is an excellent opportunity to work on a modern Azure and Snowflake data platform, helping to deliver scalable data pipelines, analytics capabilities and business-critical integrations.
The Role
You\'ll work closely with Business Analysts, Developers, Testers and business stakeholders to design and deliver high-quality data engineering solutions. This role combines hands-on engineering with stakeholder engagement and requires someone who enjoys solving complex data challenges within a fast-paced investment management environment.
Key Responsibilities
- Design, build and maintain scalable data pipelines and ETL/ELT solutions
- Develop robust data models and transformations using Snowflake and dbt
- Build and optimise data integrations across multiple platforms and applications
- Work with Azure Data Factory and Databricks to develop modern cloud data solutions
- Develop Python-based automation and data processing solutions
- Write high-performance SQL for data extraction, transformation and reporting
- Work alongside Business Analysts to translate business requirements into technical solutions
- Participate throughout the full software development lifecycle
- Perform testing and support business user acceptance
- Ensure data quality, governance and best engineering practices are followed
- Contribute to continuous improvement of the data platform and engineering standards
Essential Skills & Experience
- Strong cloud data engineering expertise, ideally within Financial Services or Asset Management
- Snowflake (essential)
- dbt for data transformation (essential)
- Python
- Azure Data Factory
- Azure Databricks
- SQL Server
- Advanced SQL development
- ETL / ELT pipeline development
- Cloud-based data engineering
- Data modelling
- API and data integration
- Git and Agile delivery methodologies
- Full software development lifecycle
Highly Desirable
- Experience within investment management or financial services, including exposure to one or more of the following: Front Office or Investment platforms, Asset Management, Market or reference data, ESG / Sustainability data, Bloomberg Aladdin or Aladdin Data Cloud (ADC), Power BI, Web scraping, Enterprise scheduling tools such as JAMS
About You
You'll be someone who enjoys working closely with both technology and business teams and is passionate about building modern, scalable data platforms.
- Excellent problem-solving skills
- Strong communication and stakeholder management
- A collaborative approach
- High attention to detail
- Passion for delivering quality engineering solutions
- Experience working within Agile/Scrum teams
What\'s on Offer
- Initial 4-month contract with a strong likelihood of extension
- Hybrid working
- Inside IR35
- Opportunity to work on a modern Azure & Snowflake data platform
- Collaborative Agile environment
- Work within one of the UK\'s leading investment management technology teams without the bureaucracy often found in large organisations
Data Engineer - Strike IT employer: PVH (Tommy Hilfiger/Calvin Klein)
Intapp is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration within the accounting and consulting sectors across EMEA. With a strong commitment to employee growth, Intapp provides ample opportunities for professional development and leadership coaching, ensuring that team members thrive in their careers while contributing to the company's strategic vision. The culture is built on accountability and high performance, making it an ideal place for those looking to make a significant impact in a rapidly evolving industry.
Contact Details:
PVH (Tommy Hilfiger/Calvin Klein) Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer - Strike IT
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Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at PVH (Tommy Hilfiger/Calvin Klein), make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
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Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to PVH (Tommy Hilfiger/Calvin Klein), emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
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How to prepare for a job interview at PVH (Tommy Hilfiger/Calvin Klein)
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at PVH (Tommy Hilfiger/Calvin Klein).
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at PVH (Tommy Hilfiger/Calvin Klein).
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