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- Tasks: Integrate diverse data sources into enterprise analytics platforms for AI and analytics.
- Company: Join a renowned international client in a hybrid work environment.
- Benefits: Competitive contract, flexible working, and opportunities to enhance your skills.
- Why this job: Make a real impact by supporting cutting-edge AI and analytical workloads.
- Qualifications: Experience with Snowflake, Databricks, Kafka, Python, SQL, and modern ETL/ELT tools.
- Other info: Collaborate with cross-functional teams in a dynamic and innovative setting.
The predicted salary is between 50000 - 60000 £ per year.
Are you an experienced Data Engineer with experience of Data Integration in Production Environments? I am working with an internationally renowned client who is looking for someone to help integrate diverse internal and external data sources into enterprise analytics platforms to support AI and analytical workloads. The role exists to translate business and user needs into robust data structures and pipelines that downstream developers, analysts and UX teams can rely on. You will work with cross-functional stakeholders to ensure data is well modelled and clearly understood by its consumers.
I am therefore keen to speak with candidates who have:
- Hands-on experience integrating data into Snowflake and Databricks in production environments.
- Strong working knowledge of Kafka, Python and SQL.
- Experience building and maintaining data pipelines using modern ETL/ELT tools.
- Familiarity with Git-based development workflows.
- Experience with visualisation or monitoring tools such as Power BI and Grafana.
- Solid grounding in big data engineering and data analytics principles.
- Experience supporting AI or ML inference pipelines and collaborating with UX or front-end teams.
- Strong documentation and communication skills in a cross-functional environment.
Data Integration Engineer employer: Henderson Scott
Contact Detail:
Henderson Scott Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Integration Engineer
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with Snowflake or Databricks. A friendly chat can lead to insider info about job openings that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data integration projects, especially those involving Kafka, Python, and SQL. This will give potential employers a clear view of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of ETL/ELT tools and big data principles. Be ready to discuss how you've built and maintained data pipelines in production environments – real-world examples go a long way!
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented Data Integration Engineers like you. Plus, it’s a great way to ensure your application gets noticed by the right people.
We think you need these skills to ace Data Integration Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Snowflake, Databricks, and any relevant data integration projects. We want to see how your skills match the job description, so don’t be shy about showcasing your hands-on experience!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the Data Integration Engineer role. Share specific examples of your work with data pipelines and how you've collaborated with cross-functional teams.
Showcase Your Technical Skills: Don’t forget to mention your proficiency in Kafka, Python, SQL, and any ETL/ELT tools you’ve used. We love seeing candidates who can demonstrate their technical know-how, so include any relevant projects or achievements!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the process smoother for everyone involved!
How to prepare for a job interview at Henderson Scott
✨Know Your Tech Stack
Make sure you brush up on your experience with Snowflake, Databricks, Kafka, Python, and SQL. Be ready to discuss specific projects where you've used these technologies, as well as any challenges you faced and how you overcame them.
✨Showcase Your Data Pipeline Skills
Prepare to talk about your experience building and maintaining data pipelines. Highlight any modern ETL/ELT tools you've used and be ready to explain the architecture of a pipeline you've developed, including how it supports AI or ML workloads.
✨Communicate Clearly
Since this role involves working with cross-functional teams, practice explaining complex technical concepts in simple terms. Think about how you can demonstrate your strong documentation skills and how you ensure that data is well modelled and understood by its consumers.
✨Familiarise Yourself with Visualisation Tools
If you've worked with Power BI or Grafana, be prepared to discuss how you've used these tools to monitor data pipelines or visualise data for stakeholders. If you haven't, consider doing a bit of research or even a quick tutorial to understand their functionalities.