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- Tasks: Lead quality assurance for data platforms, ensuring stability and compliance.
- Company: Join AstraZeneca, a global leader in healthcare innovation.
- Benefits: Enjoy flexible working options and a collaborative culture.
- Why this job: Be empowered to drive change and enhance data engineering processes.
- Qualifications: Bachelor's degree in Computer Science; 8-12 years in data engineering required.
- Other info: Opportunity to work with cutting-edge technologies in a dynamic environment.
The predicted salary is between 54000 - 84000 £ per year.
Join our Commercial IT Data Analytics & AI (DAAI) team as a Product Quality Data Engineer, where you will play a pivotal role in ensuring the quality and stability of our data platforms built on AWS services, Databricks, and Snaplogic. Based in Chennai GITC, you will be implementing the quality engineering strategy, enforcing quality standards, and contributing to the overall success of our data platform.
Are you ready to take on more ownership and be empowered to lead?
Accountabilities:
- Implementing data and data engineering quality assurance strategies.
- Establishing and maintaining quality standards in design, code, and data model.
- Collaborating with Product Engineers and the DevOps team to share and apply quality engineering standards across all product releases.
- Understanding the application development processes of AstraZeneca’s implementation of the data product.
- Adopting new technologies and tools to enhance data engineering processes and efficiency.
Essential Skills/Experience:
- Bachelor’s degree or equivalent in Computer Engineering, Computer Science, or a related field.
- 8 to 12 years of data engineering with proven experience in a product quality engineering or similar role.
- Experience of working within a quality and compliance environment.
- Broad understanding of cloud architecture (preferably in AWS).
- Strong experience in Databricks, Pyspark and the AWS suite of applications.
- Proficiency in programming languages such as Python.
- Experienced in Agile Development techniques and Methodologies.
- Solid understanding of data modelling, ETL processes and data warehousing concepts.
- Excellent communication and leadership skills.
- Experience with big data technologies such as Hadoop or Spark.
- Certification in AWS or Databricks.
- Prior significant experience working in Pharmaceutical or Healthcare industry IT environment.
Ready to join us at a crucial stage of our journey in becoming a digital and data-led enterprise? Apply now!
Senior Consultant - Product Quality Data Engineer employer: AstraZeneca GmbH
Contact Detail:
AstraZeneca GmbH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Consultant - Product Quality Data Engineer
✨Tip Number 1
Familiarise yourself with AWS services and Databricks, as these are crucial for the role. Consider taking online courses or certifications to deepen your understanding, which will not only boost your confidence but also demonstrate your commitment to potential employers.
✨Tip Number 2
Network with professionals in the data engineering field, especially those who have experience in quality assurance. Attend industry meetups or webinars to connect with others and gain insights into best practices that you can mention during interviews.
✨Tip Number 3
Stay updated on the latest trends in data engineering and quality assurance. Follow relevant blogs, podcasts, and forums to gather knowledge that you can bring up in conversations with our team, showcasing your passion for the field.
✨Tip Number 4
Prepare to discuss your previous experiences in implementing quality standards and collaborating with cross-functional teams. Be ready to share specific examples that highlight your leadership skills and technical expertise, as these will be key in demonstrating your fit for the role.
We think you need these skills to ace Senior Consultant - Product Quality Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering and quality assurance. Emphasise your expertise with AWS, Databricks, and programming languages like Python, as these are crucial for the role.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the position and how your background aligns with the responsibilities outlined in the job description. Mention specific projects or experiences that demonstrate your ability to implement quality engineering strategies.
Showcase Technical Skills: Clearly list your technical skills related to cloud architecture, data modelling, and big data technologies. Providing examples of how you've used these skills in previous roles can strengthen your application.
Highlight Leadership Experience: Since the role involves collaboration and leadership, be sure to include any relevant leadership experiences. Discuss how you've led teams or projects, particularly in Agile environments, to showcase your capability to take ownership.
How to prepare for a job interview at AstraZeneca GmbH
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with AWS, Databricks, and Pyspark in detail. Highlight specific projects where you implemented quality engineering strategies and how they contributed to the success of data platforms.
✨Demonstrate Your Understanding of Quality Standards
Familiarise yourself with quality assurance methodologies relevant to data engineering. Be ready to explain how you have established and maintained quality standards in previous roles, particularly in a compliance-driven environment.
✨Emphasise Collaboration Skills
Since the role involves working closely with Product Engineers and the DevOps team, prepare examples that showcase your ability to collaborate effectively. Discuss how you’ve shared quality engineering standards across teams in past experiences.
✨Prepare for Behavioural Questions
Expect questions about your leadership style and how you handle challenges in a team setting. Use the STAR method (Situation, Task, Action, Result) to structure your responses, focusing on your contributions to team success.
