At a Glance
- Tasks: Join us as a Senior Data Engineer I, building secure and scalable data infrastructures.
- Company: Elsevier is a global leader in information and analytics, enhancing science and healthcare.
- Benefits: Enjoy flexible working hours, remote options, generous holiday allowance, and wellbeing programs.
- Why this job: Be part of a collaborative team driving impactful data solutions for a better world.
- Qualifications: Experience with modern data stack technologies and strong Python and SQL skills required.
- Other info: We promote diversity and inclusivity, ensuring everyone has a voice and opportunity to thrive.
The predicted salary is between 48000 - 84000 £ per year.
About the Team:
The Academic Information Systems ( AI S) DataOps team is a shared technology group responsible for building, administering, governing, and setting standards for a growing number of strategic data platforms and services. Our capabilities enable data to be extracted, centralized, transformed, transmitted, and analyzed across a range of products in the AIS space. Due to our footprint across the enterprise, we are relied upon to ensure our systems are trusted, reliable and available. The technology underpinning these capabilities includes industry leading data and analytics products such as Snowflake, Astronomer/Airflow, Kubernetes , DBT, Tableau, Sisense , Collibra, and Kafka/ Debezium . Our mission is to enable frictionless experiences for our AIS colleagues and customers so that they can openly and securely consume trustworthy data, enhancing everyday interactions and decisions.
About the Role:
As a S enior Data Engineer I , you will be responsible for helping to creat e a data infrastructure that is secure, scalable, well-connected, thoughtfully architected while also building a deep domain knowledge of our business domain. This team is responsible for the complex flow of data across teams, data center s , and organizational boundaries all around the world . This data is the backbone of successful storytelling for AIS colleagues and customers, and it m u st be curated through several reliable yet cost-effective approaches.
Responsibilities:
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Build and maintain a robust, modern data orchestration and transformation architecture to support both batch and streaming processes.
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Ensure reliable delivery of clean, accurate data for analytical platforms and data sharing services.
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Contribute to the development and enforcement of technical and coding standards to mature SDLC practices.
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Collaborate with DevOps to automate deployments and implement Infrastructure as Code (IaC) for consistent, repeatable environments across regions.
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Develop modularized components and reusable frameworks, establishing common patterns for easy contribution and reliable deployment.
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Document and promote best practices by establishing guidelines with stakeholders and sharing knowledge across engineering and product teams.
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Drive operational efficiency, reliability, and scalability through improvements in logging, monitoring, and observability.
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Support platform evolution and data governance by identifying capability gaps, implementing necessary tooling and processes, and promoting DataOps through leadership and user feedback initiatives.
Requirements:
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Deploy and govern modern data stack technologies (e.g., Snowflake, Airflow, DBT, Fivetran, Airbyte, Tableau, Sisense, AWS, GitHub, Terraform, Docker) at enterprise scale for data engineering workloads.
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Develop deployable, reusable ETL/ELT solutions using Python, advanced SQL, and Jinja for data pipelines and stored procedures.
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Demonstrate applied understanding of SDLC best practices and contribute to the maturity of SDLC, DataOps, and DevOps processes.
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Participate actively in Agile delivery, including ceremonies, requirements refinement, and fostering a culture of iterative improvement.
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Provide thought leadership in the data platform landscape by building well-researched proposals and driving adoption of change.
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Design comprehensive technical solutions, producing architecture and infrastructure documentation for scalable, secure, and efficient data platforms.
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Exhibit deep expertise in AWS data and analytics services, with experience in production-grade cloud solutions and cost optimization.
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Apply strong data and technology governance, ensuring compliance with data management, privacy, and security practices, while collaborating cross-functionally and adapting to evolving priorities.
Work in a way that works for you
We promote a healthy work/life balance across the organization . With an average length of service of 9 years, we are confident that we offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and long-term goals.
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Working remotely from home or in our office in a flexible hybrid style
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Working flexible hours – flexing the times when you work in the day to help you fit everything in and work when you are the most productive
Working with us
We are an equal opportunity employer with a commitment to help you succeed. Here, you will find an inclusive, agile, collaborative, innovative and fun environment, where everyone has a part to play. Regardless of the team you join, we promote a diverse environment with co-workers who are passionate about what they do, and how they do it.
Working for you
At Elsevier, we know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer:
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Generous holiday allowance with the option to buy additional days
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Access to learning platforms and encouragement to book up to 10 days focused learning/development time per year
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Health screening, eye care vouchers and private medical benefits
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Wellbeing programs
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Life assurance
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Access to a competitive contributory pension scheme
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Long service awards
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Save As You Earn share option scheme
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Travel Season ticket loan
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Maternity, paternity and shared parental leave
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Access to emergency care for both the elderly and children
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RELX Cares days, giving you time to support the charities and causes that matter to you
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Access to employee resource groups with dedicated time to volunteer
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Access to extensive learning and development resources
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Access to employee discounts via Perks at Work
About the business
A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world\’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.
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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
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Senior Data Engineer I employer: Elsevier
Contact Detail:
Elsevier 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 technologies mentioned in the job description, such as Snowflake, Airflow, and DBT. Having hands-on experience or projects showcasing your skills with these tools can set you apart from other candidates.
✨Tip Number 2
Engage with the data engineering community online. Join forums, attend webinars, or participate in discussions related to DataOps and modern data stacks. This not only enhances your knowledge but also helps you network with professionals who might provide insights or referrals.
✨Tip Number 3
Prepare to discuss your experience with Agile methodologies during the interview. Be ready to share examples of how you've contributed to Agile ceremonies and fostered a culture of iterative improvement in previous roles.
✨Tip Number 4
Showcase your understanding of data governance and compliance. Be prepared to discuss how you've implemented data management practices in past projects, as this is crucial for the role and will demonstrate your alignment with the company's values.
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 Senior Data Engineer I role. Focus on your expertise in data orchestration, transformation architecture, and any specific technologies mentioned in the job description, such as Snowflake or Airflow.
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 previous experiences have prepared you to contribute to the AIS DataOps team and improve data governance and operational efficiency.
Showcase Technical Skills: In your application, clearly outline your technical skills, especially those related to modern data stack technologies like AWS, Python, and SQL. Provide examples of projects where you've successfully implemented these skills to solve complex data challenges.
Highlight Collaboration Experience: Emphasise your ability to work collaboratively in Agile environments. Mention any experience you have with cross-functional teams, DevOps practices, or contributing to SDLC processes, as this is crucial for the role.
How to prepare for a job interview at Elsevier
✨Know Your Tech Stack
Familiarise yourself with the technologies mentioned in the job description, such as Snowflake, Airflow, and DBT. Be prepared to discuss your experience with these tools and how you've used them in past projects.
✨Demonstrate Your Problem-Solving Skills
Prepare to showcase your ability to tackle complex data challenges. Think of specific examples where you've built or improved data pipelines, and be ready to explain your thought process and the impact of your solutions.
✨Showcase Collaboration Experience
Since the role involves working across teams, highlight your experience in collaborative environments. Discuss how you've worked with DevOps or other teams to implement Infrastructure as Code or improve data governance.
✨Emphasise Agile Methodologies
Be ready to talk about your experience with Agile practices. Share examples of how you've participated in Agile ceremonies and contributed to iterative improvements in your previous roles.