At a Glance
- Tasks: Design and build AI-driven data integrations, focusing on Salesforce.
- Company: Join Epicor, a leader in innovative technology solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with potential for career advancement in a tech-driven environment.
- Why this job: Make an impact by optimising data workflows and integrating cutting-edge AI technologies.
- Qualifications: Strong SQL skills and experience in data pipeline development required.
The predicted salary is between 60000 - 80000 £ per year.
Epicor is seeking a Senior Data & Integration Engineer in the United Kingdom to design, build, and scale AI-driven data integrations across our platform, with Salesforce as a core system.
The role blends backend and data engineering with AI integration.
You will design scalable backend services, develop Salesforce integrations, and optimize ETL pipelines, data workflows, and event-driven architectures.
Strong SQL and data pipeline experience are essential.
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Senior Data & AI Integration Engineer (Salesforce) in England employer: Epicor
Epicor is an excellent employer that fosters a collaborative and innovative work culture, where employees are encouraged to grow their skills in cutting-edge technologies like AI and data integration. With a strong focus on professional development and a commitment to work-life balance, our UK team enjoys unique opportunities to contribute to impactful projects while being part of a supportive community. Join us to be at the forefront of technology in a role that promises both challenge and reward.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data & AI Integration Engineer (Salesforce) in England
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Epicor.
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We think you need these skills to ace Senior Data & AI Integration Engineer (Salesforce) in England
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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Craft a Tailored Cover Letter:For a full-time role at Epicor, 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 Epicor. 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 Epicor
✨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!
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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
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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.
