At a Glance
- Tasks: Design and build scalable data pipelines for AI-driven projects.
- Company: Join Moody’s, a leader in digital content and data solutions.
- Benefits: Competitive salary, flexible work options, and growth opportunities.
- Other info: Collaborative environment with a focus on innovation and data quality.
- Why this job: Be at the forefront of AI technology and make a real impact.
- Qualifications: Experience with data engineering tools and strong problem-solving skills.
The predicted salary is between 60000 - 80000 £ per year.
Moody’s is seeking a data engineer to design, build, and support highly scalable data pipelines powering its next‑generation digital content platform.
You will work with Data Bricks, Snowflake, Apache Airflow, dbt (SQL), and Python within AWS, collaborating with cross‑functional teams to understand data needs and deliver scalable solutions.
The role emphasizes data quality, governance, and actionable insights for AI‑driven workloads.
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Data Engineer for AI-Driven Data Pipelines in Manchester employer: 慨正橡扯
At 慨正橡扯, we pride ourselves on being an exceptional employer that champions innovation and collaboration in the field of Behavioral Economics and Retirement Research. Our hybrid working model not only offers flexibility but also nurtures a vibrant work culture where employees are encouraged to grow and develop their skills through meaningful projects and leadership opportunities. Join us in Europe, where your expertise will directly contribute to enhancing investor outcomes and shaping impactful business strategies.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer for AI-Driven Data Pipelines in Manchester
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We think you need these skills to ace Data Engineer for AI-Driven Data Pipelines in Manchester
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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✨Prepare for Case Studies
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