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- Tasks: Lead data engineering projects, crafting innovative data pipelines and solutions.
- Company: Join IFS, a billion-dollar company revolutionising AI technology in enterprise software.
- Benefits: Enjoy flexible hybrid work options and a diverse, inclusive workplace culture.
- Why this job: Be part of a global team making a real impact with cutting-edge AI solutions.
- Qualifications: 7+ years in data engineering, skilled in cloud technologies and advanced analytics.
- Other info: Engage in continuous learning and community-building while driving innovation.
The predicted salary is between 60000 - 84000 £ per year.
IFS is a billion-dollar revenue company with 7000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters–at the Moment of Service. Our commitment to internal AI adoption has allowed us to stay at the forefront of technological advancements, ensuring our colleagues can unlock their creativity and productivity, and our solutions are always cutting-edge.
We help solve some of society’s greatest challenges, fostering a better future through our agility, collaboration, and trust. We celebrate diversity and understand our responsibility to reflect the diverse world we work in. We are committed to promoting an inclusive workforce that fully represents the many different cultures, backgrounds, and viewpoints of our customers, our partners, and our communities.
Are you ready to make waves in the world of AI? We're on the hunt for a Principal Data Engineer to join our dynamic global R&D organization. We're looking for someone who brings the heat, fosters seamless collaboration, and is always chasing that next level of excellence. You'll be at the forefront of infusing cutting-edge advanced analytics and AI into IFS Cloud, revolutionizing Enterprise Resource Planning, Asset Management, and Field Service Management.
Your data engineer wizardry will power our solutions, crafting efficient data pipelines, expanding our data platform capabilities, and pushing the envelope of data-driven innovation across our product lineup. Your sharp critical thinking and knack for real-world business dilemmas will be instrumental in orchestrating end-to-end solutions.
This role is all about hands-on technical prowess, and we expect you to bring your A-game. Your mission includes:
- Spotting high-value data opportunity within our IFS offerings, translating raw data into powerful features and reusable data assets.
- Serving as our data expert, guiding us towards the latest and greatest data technology and platform trends.
- Leading the Data Engineering team in crafting and integrating data projects from the ground up.
- Locking arms with ML Engineers, Data Scientists, Architects, and Product/Program Managers to define, create, deploy, monitor, and document data pipelines to power advanced AI solutions.
- Becoming our data technology evangelist, sharing your discoveries with clients and internal stakeholders, offering actionable insights that drive change.
To succeed in this role, you'll need:
- 7+ years of data engineering experience, skilled in scalable solutions like Data Lakes/Lakehouse, Graph and Vector Databases (e.g., ADLS, Elasticsearch, MongoDB, Azure AI search, etc.).
- Proficient in data pipelines across cloud/on-premises, using Azure and other technologies.
- Experienced in orchestrating data workflows and Kubernetes clusters on AKS using Airflow, Kubeflow, Argo, Dagster or similar.
- Skilled with data ingestion tools like Airbyte, Fivetran, etc. for diverse data sources.
- Expert in large-scale data processing with Spark or Dask.
- Strong in Python, Scala, C# or Java, cloud SDKs and APIs.
- AI/ML expertise for pipeline efficiency, familiar with TensorFlow, PyTorch, AutoML, Python/R, and MLOps (MLflow, Kubeflow).
- Solid in DevOps, CI/CD automation with Bitbucket Pipelines, Azure DevOps, GitHub.
- Experienced in leveraging Azure AI Search, Elasticsearch, MongoDB or other hybrid/vector stores for content analysis and indexing.
- Proficiency in building IoT data pipelines, encompassing real-time data ingestion, transformation, security, scalability, and seamless integration with IoT platforms.
- Design, develop, and monitor streaming data applications using Kafka and related technologies.
We embrace flexibility and hybrid work opportunities to support diverse needs and lifestyles, while also valuing inclusive workplace experiences. By fostering a sense of community, we drive innovation, strengthen connections, and nurture belonging.
Sounds exciting? Are you ready for the market leader in FSM? Then we look forward to receiving your complete application through our online applicant management system, stating your salary requirements and earliest possible starting date.
Principal Data Engineer employer: IFS
Contact Detail:
IFS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Engineer
✨Tip Number 1
Familiarise yourself with IFS's AI-driven solutions and their impact on enterprise software. Understanding how your role as a Principal Data Engineer can contribute to their mission will help you articulate your value during discussions.
✨Tip Number 2
Network with current employees or alumni who work at IFS. Engaging in conversations about their experiences can provide insights into the company culture and expectations, which can be invaluable during interviews.
✨Tip Number 3
Stay updated on the latest trends in data engineering, particularly around AI and machine learning. Being able to discuss recent advancements or case studies can demonstrate your passion and expertise in the field.
✨Tip Number 4
Prepare to showcase your hands-on experience with relevant technologies mentioned in the job description. Be ready to discuss specific projects where you've successfully implemented scalable data solutions or advanced analytics.
We think you need these skills to ace Principal Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with scalable solutions and cloud technologies. Use keywords from the job description to demonstrate your fit for the role.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for AI and data engineering. Mention specific projects or achievements that align with IFS's focus on advanced analytics and AI-driven solutions.
Showcase Technical Skills: In your application, clearly outline your technical skills, especially those mentioned in the job description such as Python, Spark, and Azure. Provide examples of how you've used these skills in previous roles.
Highlight Collaboration Experience: Since the role involves working closely with various teams, emphasise your experience in collaborative projects. Share examples of how you’ve successfully worked with cross-functional teams to achieve common goals.
How to prepare for a job interview at IFS
✨Showcase Your Technical Skills
As a Principal Data Engineer, you'll need to demonstrate your expertise in data engineering. Be prepared to discuss your experience with scalable solutions, data pipelines, and the specific technologies mentioned in the job description, such as Azure, Spark, and Kubernetes.
✨Highlight Collaboration Experience
This role emphasises teamwork with ML Engineers, Data Scientists, and other stakeholders. Share examples of how you've successfully collaborated on projects, showcasing your ability to work autonomously while also being a team player.
✨Prepare for Problem-Solving Scenarios
Expect to tackle real-world business dilemmas during the interview. Prepare to discuss how you've approached complex data challenges in the past, including your thought process and the solutions you implemented.
✨Demonstrate Your Passion for AI and Innovation
IFS is looking for innovative thinkers who can push the envelope. Be ready to share your thoughts on the latest trends in AI and data technology, and how you envision contributing to IFS's mission of making a positive impact through advanced analytics.
