At a Glance
- Tasks: Build scalable data infrastructure for AI-driven products and audience intelligence.
- Company: Join a forward-thinking company focused on innovative data solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Collaborative environment with excellent career advancement opportunities.
- Why this job: Shape the future of data engineering and make a real impact in tech.
- Qualifications: Strong Python and SQL skills, with experience in data pipeline development.
Accepting applications until: 7 August 2026
Job Description
Your role: Data Engineer
A hands-on role building scalable data infrastructure that powers AI-driven products and audience intelligence.
Key Responsibilities
- Data Platform & Pipeline Engineering (60%): Design, build and maintain scalable batch and near real-time pipelines across ingestion, transformation and serving layers. Develop reusable data models and optimise performance, reliability and cost.
- Platform Evolution & Engineering Excellence (20%): Shape the Global:IQ data platform through best practices in architecture, tooling, CI/CD and infrastructure as code. Create reusable components and maintain clear technical documentation.
- Quality & Governance (10%): Implement robust data validation, testing, lineage and observability to ensure high-quality, trusted datasets. Support governance and privacy-conscious data handling.
- Collaboration & Enablement (10%): Partner with Data Science, MLOps, Product and commercial teams to deliver production-ready data solutions. Support and mentor others while communicating clearly with stakeholders.
What You'll Love About This Role
- Think Big: Build a data platform from the ground up that will scale with a cutting-edge AI and ML product.
- Own It: Take responsibility for production-grade data systems that directly power targeting, optimisation and measurement.
- Keep it Simple: Apply pragmatic engineering to deliver reliable, maintainable solutions without over-engineering.
- Better Together: Work in a highly collaborative, cross-functional team spanning technical and commercial expertise.
What Success Looks Like
In your first few months, you'll have:
- Developed a strong understanding of the Global:IQ platform and its core use cases
- Successfully onboarded key datasets with robust ingestion and quality standards
- Delivered reliable pipelines supporting live production use casesEstablished or improved data engineering standards and best practices
- Built strong working relationships across Data, Product and commercial teams
- Identified opportunities to improve scalability, reliability and efficiency
What You'll Need
- Programming & Data Skills: Strong Python and SQL skills, with experience building production-grade data pipelines
- Data Platform Experience: Hands-on experience with modern data tools (e.g. Snowflake, Airflow, dbt) and cloud environments (preferably AWS)
- Engineering Best Practice: Knowledge of CI/CD, testing, version control and infrastructure as code
- Data Quality & Governance: Understanding of observability, validation and maintaining reliable data systems
- Collaboration & Communication: Ability to translate business and data science needs into scalable solutions and communicate clearly with stakeholders
- Mindset & Approach: Pragmatic, ownership-driven and curious, with a passion for building impactful data products
Data Engineer 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
✨Get Involved in Data Science Meetups
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✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Engineer at PVH (Tommy Hilfiger/Calvin Klein).
✨Leverage Professional Networks
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When you find a suitable opening like Data Engineer at PVH (Tommy Hilfiger/Calvin Klein), make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Engineer
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!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at PVH (Tommy Hilfiger/Calvin Klein), your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at PVH (Tommy Hilfiger/Calvin Klein). Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at PVH (Tommy Hilfiger/Calvin Klein)
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at PVH (Tommy Hilfiger/Calvin Klein)!
✨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.
