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- Tasks: Design, build, and maintain high-performance data pipelines using tools like Dagster and Python.
- Company: Join a pioneering company in data intelligence that empowers businesses with transformative insights.
- Benefits: Work with cutting-edge technology and collaborate with talented data teams.
- Why this job: Be part of a team that shapes the future of data solutions and enhances your technical skills.
- Qualifications: 3+ years of Data Engineering experience, strong Python skills, and expertise in cloud platforms like AWS.
- Other info: Bonus points for experience in predictive analytics and version control tools!
The predicted salary is between 43200 - 72000 £ per year.
A leading provider of technology-driven data solutions that empower businesses with transformative insights, this company is a pioneer in data intelligence and is currently seeking to build a new, predictive model. In this role, you will design, build, and maintain high-performance data pipelines using tools like Dagster and Python. You’ll process diverse data sources, collaborate with data teams, and optimize data workflows for both real-time and batch processing. You’ll also contribute to data architecture, ensure data governance and security, and maintain comprehensive documentation. Technical Skills: Proficiency in pipeline orchestration tools (e.g., Dagster, Airflow) Strong Python programming skills with experience in libraries like Pandas and PySpark Expertise in cloud platforms, particularly AWS (e.g., S3, Lambda, Redshift, RDS) Deep understanding of data modeling, ETL workflows, and scalable architecture design Familiarity with integrating machine learning models into production workflows Experience: 3+ years of experience in a Data Engineering role, with experience in mid-to-senior capacity Proven track record of working with live datasets and building end-to-end data pipelines Strong SQL skills for querying and managing large datasets Hands-on experience in creating architectural diagrams and delivering technical presentations A big bonus if you have.. Experience in building and optimizing propensity models or similar predictive analytics models Strong understanding of feature engineering, predictive modeling, and evaluation metrics Experience with version control tools (e.g., Git) and CI/CD pipelines Intrigued? Drop me a message!
Data Engineer employer: Trust In SODA
Contact Detail:
Trust In SODA Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Familiarize yourself with the specific tools mentioned in the job description, like Dagster and Python. Consider building a small project that showcases your ability to create data pipelines using these technologies, as this will demonstrate your hands-on experience.
✨Tip Number 2
Network with current or former employees of the company on platforms like LinkedIn. Engaging in conversations about their experiences can provide you with valuable insights into the company culture and expectations for the Data Engineer role.
✨Tip Number 3
Prepare to discuss your previous projects involving live datasets and end-to-end data pipelines during the interview. Be ready to explain the challenges you faced and how you overcame them, as this will highlight your problem-solving skills.
✨Tip Number 4
Stay updated on the latest trends in data engineering and predictive modeling. Being able to discuss recent advancements or case studies in these areas during your interview can set you apart from other candidates.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description and understand the key responsibilities and required skills. Highlight your experience with data pipelines, Python, and cloud platforms like AWS in your application.
Tailor Your CV: Customize your CV to emphasize relevant experience in Data Engineering. Include specific projects where you designed and maintained data pipelines, and mention any tools like Dagster or Airflow that you have used.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of the company's mission. Mention how your skills align with their needs, especially in predictive modeling and data governance.
Showcase Technical Skills: In your application, clearly outline your technical skills, particularly in Python, SQL, and cloud services. Provide examples of how you've utilized these skills in past roles to solve complex data challenges.
How to prepare for a job interview at Trust In SODA
✨Showcase Your Technical Skills
Be prepared to discuss your proficiency in pipeline orchestration tools like Dagster and Airflow. Highlight specific projects where you've utilized Python, especially with libraries like Pandas and PySpark, to demonstrate your hands-on experience.
✨Discuss Your Experience with Data Pipelines
Share examples of end-to-end data pipelines you've built or optimized. Emphasize your experience with live datasets and how you ensured data governance and security throughout the process.
✨Prepare for Technical Questions
Expect questions related to data modeling, ETL workflows, and scalable architecture design. Brush up on your SQL skills and be ready to solve problems or answer scenario-based questions that test your understanding of these concepts.
✨Highlight Collaboration and Documentation Skills
Since this role involves working with data teams, be sure to mention your collaborative experiences. Discuss how you maintain comprehensive documentation and how it has benefited your previous projects.
