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- Tasks: Build and maintain a modern data infrastructure for seamless data flow and analytics.
- Company: Join a leading social network focused on innovative data solutions and storytelling.
- Benefits: Enjoy remote work options, flexible hours, wellbeing initiatives, and study assistance.
- Why this job: Be part of a dynamic team driving data governance and operational efficiency in a collaborative culture.
- Qualifications: Experience with modern data stack technologies and strong skills in Python and SQL required.
- Other info: Flexible hybrid working style with a focus on work/life balance.
The predicted salary is between 43200 - 72000 £ per year.
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Senior Data Engineer I
As a Senior Data Engineer I, you will be responsible for helping to create a data infrastructure that is secure, scalable, well-connected, and thoughtfully architected. You will build a deep domain knowledge of our business domain. This team manages the complex flow of data across teams, data centers, and organizational boundaries worldwide. The data is crucial for successful storytelling for AIS colleagues and customers, and it must be curated through reliable and cost-effective approaches.
Responsibilities:
- Build and maintain a robust, modern data orchestration and transformation architecture supporting batch and streaming processes.
- Ensure reliable delivery of clean, accurate data for analytical platforms and sharing services.
- Contribute to developing and enforcing technical and coding standards to mature SDLC practices.
- Collaborate with DevOps to automate deployments and implement Infrastructure as Code (IaC) for consistent environments across regions.
- Develop modular components and reusable frameworks, establishing common patterns for contribution and deployment.
- Document and promote best practices, establishing guidelines with stakeholders and sharing knowledge across teams.
- Drive operational efficiency, reliability, and scalability through improved logging, monitoring, and observability.
- Support platform evolution and data governance by identifying gaps, implementing tooling, and promoting DataOps via leadership and feedback initiatives.
Requirements:
- Experience deploying and governing modern data stack technologies (e.g., Snowflake, Airflow, DBT, Fivetran, Airbyte, Tableau, Sisense, AWS, GitHub, Terraform, Docker) at an enterprise scale.
- Develop deployable, reusable ETL/ELT solutions using Python, advanced SQL, and Jinja for data pipelines and stored procedures.
- Understanding of SDLC best practices, contributing to DataOps and DevOps process maturity.
- Active participation in Agile ceremonies, requirements refinement, and fostering iterative improvement.
- Provide thought leadership by building well-researched proposals and driving adoption of new technologies.
- Design technical solutions with comprehensive documentation for scalable, secure data platforms.
- Deep expertise in AWS data and analytics services, with experience in production cloud solutions and cost optimization.
- Strong data and technology governance, ensuring compliance with data management, privacy, and security standards, while collaborating cross-functionally.
Work in a way that works for you
We promote a healthy work/life balance. With an average service length of 9 years, we offer an appealing working environment. We support your immediate responsibilities and long-term goals with wellbeing initiatives, shared parental leave, study assistance, and sabbaticals.
Work remotely from home or in our office in a flexible hybrid style.
Enjoy flexible hours, adjusting your work times to maximize productivity.
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Senior Data Engineer I employer: Elsevier Limited Company
Contact Detail:
Elsevier Limited Company Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer I
✨Tip Number 1
Familiarise yourself with the specific data stack technologies mentioned in the job description, such as Snowflake and Airflow. Having hands-on experience or projects showcasing these tools can significantly boost your chances.
✨Tip Number 2
Engage with the data engineering community online. Join forums or LinkedIn groups where professionals discuss best practices and trends. This can help you gain insights and potentially connect with someone at StudySmarter.
✨Tip Number 3
Prepare to discuss your experience with Agile methodologies during interviews. Highlight any specific instances where you've contributed to iterative improvements or participated in Agile ceremonies, as this aligns with our team culture.
✨Tip Number 4
Showcase your ability to document and promote best practices in data governance. Be ready to share examples of how you've implemented compliance measures in previous roles, as this is crucial for the position.
We think you need these skills to ace Senior Data Engineer I
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the responsibilities of a Senior Data Engineer I. Focus on your expertise in data orchestration, transformation architecture, and any specific technologies mentioned in the job description.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of the company's needs. Mention specific projects or experiences that demonstrate your ability to build scalable data solutions and your familiarity with the modern data stack.
Showcase Technical Skills: In your application, clearly outline your technical skills, especially those related to the required technologies like Snowflake, Airflow, and AWS. Provide examples of how you've successfully implemented these technologies in past roles.
Highlight Collaboration Experience: Emphasise your experience working in cross-functional teams and participating in Agile ceremonies. This role requires collaboration with DevOps and other stakeholders, so showcasing your teamwork skills will be beneficial.
How to prepare for a job interview at Elsevier Limited Company
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with modern data stack technologies like Snowflake, Airflow, and AWS. Highlight specific projects where you've deployed these technologies at an enterprise scale, as this will demonstrate your capability to handle the responsibilities of the role.
✨Demonstrate Your Problem-Solving Skills
Expect questions that assess your ability to identify gaps in data governance and operational efficiency. Prepare examples of how you've implemented tooling or improved processes in previous roles, showcasing your proactive approach to problem-solving.
✨Emphasise Collaboration and Communication
Since the role involves working cross-functionally, be ready to discuss your experience in Agile ceremonies and how you've collaborated with DevOps teams. Share examples of how you’ve documented best practices and shared knowledge across teams to foster a collaborative environment.
✨Prepare for Scenario-Based Questions
You might face scenario-based questions that require you to design technical solutions or propose new technologies. Practice articulating your thought process clearly, ensuring you cover aspects like scalability, security, and compliance with data management standards.
