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- Tasks: Design and maintain high-performance data pipelines using tools like Dagster and Python.
- Company: Join a pioneering company in data intelligence, transforming businesses with innovative data solutions.
- Benefits: Work with cutting-edge technology and collaborate with talented data teams.
- Why this job: Be part of a dynamic team shaping the future of data architecture and governance.
- Qualifications: 3+ years in Data Engineering, strong Python skills, and experience with cloud platforms like AWS.
- Other info: Bonus points for experience in predictive analytics and version control tools!
The predicted salary is between 48000 - 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! 📩
Trust In SODA | Data Engineer employer: Trust In SODA
Contact Detail:
Trust In SODA Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Trust In SODA | 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 or contributing to an open-source project that utilizes these technologies to showcase your hands-on experience.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who have experience with AWS and data pipeline orchestration. Engaging in relevant online communities or attending meetups can help you gain insights and potentially get referrals.
✨Tip Number 3
Prepare to discuss your previous projects in detail, particularly those involving live datasets and end-to-end data pipelines. Be ready to explain your thought process, challenges faced, and how you optimized workflows.
✨Tip Number 4
If you have experience with predictive modeling or feature engineering, be sure to highlight this in conversations. Prepare examples of how you've integrated machine learning models into production workflows, as this is a big bonus for the role.
We think you need these skills to ace Trust In SODA | 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. Tailor your application to highlight your experience with data pipelines, Python, and cloud platforms like AWS.
Highlight Relevant Experience: In your CV and cover letter, emphasize your 3+ years of experience in Data Engineering. Provide specific examples of projects where you designed and maintained data pipelines, and mention any relevant tools you've used, such as Dagster or Airflow.
Showcase Technical Skills: Clearly outline your technical skills in your application. Mention your proficiency in Python, SQL, and any experience with machine learning models or predictive analytics. If you have experience with version control tools like Git, be sure to include that as well.
Prepare a Strong Cover Letter: Craft a compelling cover letter that not only summarizes your qualifications but also expresses your enthusiasm for the role. Discuss how your background aligns with the company's mission and how you can contribute to their data solutions.
How to prepare for a job interview at Trust In SODA
✨Showcase Your Technical Skills
Be prepared to discuss your experience with pipeline orchestration tools like Dagster and Airflow. Highlight specific projects where you utilized Python, especially with libraries like Pandas and PySpark, to demonstrate your proficiency.
✨Discuss Your Experience with Cloud Platforms
Since the role requires expertise in AWS, make sure to share examples of how you've used services like S3, Lambda, Redshift, and RDS in your previous roles. This will show your familiarity with cloud environments and their applications in data engineering.
✨Prepare for Technical Questions
Expect questions related to data modeling, ETL workflows, and scalable architecture design. Brush up on these topics and be ready to explain your thought process and decision-making in past projects.
✨Highlight Collaboration and Documentation Skills
Since collaboration with data teams is crucial, share experiences where you worked effectively in a team setting. Also, emphasize your ability to maintain comprehensive documentation, as this is key for data governance and security.
