About our Team
The Enterprise Data Platforms and Services (EDPS) team are a central technology group
responsible for building, administering, governing, and setting global standards for a growing
number of Elsevier strategic data platforms and services. The capabilities we are responsible
for enable data to be collected, accessed, processed, and integrated across a wide range of
digital business solutions, used by functions including billing and order management, customer
and product master data management, and business analytics and insights delivery. 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, Tableau, Collibra, Kafka, Airflow, and
Kubernetes.
This group has been created recently as part of a longer-term strategic direction to implement
Data Mesh, and with it establish shared platforms that enables a connected collection of
enterprise-ready time saving services. Our mission is to enable frictionless experiences for all
Elsevier colleagues, so that they can openly and securely consume and produce trustworthy
data, enhancing everyday colleague and customer interactions and decisions.
About the role
We are looking for a senior engineer to build components of our Enterprise Data Platform that
are critical to both operational and analytical use cases. There will be an opportunity to work
on a modern data stack to create frictionless and trusted self-service capabilities. This role will
be expected to build standardised modules and patterns that assist Elsevier teams to onboard
and leverage various platforms capabilities. You will be expected to collaborate closely with
other technology teams to ensure that we are driving a culture of contributing towards shared
services.
Your success will ultimately be measured by your ability to deliver capabilities that successfully
meet user requirements and that all releases meet quality standards, whilst delivering to
committed timelines.
Your responsibilities
Build prototypes and proof-of-concepts ensuring we have well documented designs to
inform and support team leadership decisions while enabling more accurate sizing and
dependency mapping activities.
Support Junior developers through best practice implementation by engaging in regular
pair programming and code review sessions.
Build and design integration tools following all relevant best practices (especially
relating to security)
Developing and refining user stories for the standardised patterns and tools
Support and mentor junior members of the team and assist in building integration tools
Resolving technical system issues with integration jobs and providing root cause
analysis including urgent bug fixes
Supporting our business partners with use and implementation of standardised data
integration jobs
Collaborate with colleagues within and outside of the team and supporting them with
technical expertise
Requirements
Hands-on knowledge of the AWS Cloud ecosystem, with demonstrable experience of
building secure, production grade data solutions and applications hosted on AWS.
Extensive use of Python for programming and data manipulation, showing an ability to
develop reusable and deployable modules for ETL / ELT data pipelines, including data
orchestration.
Significant use of modern cloud database systems, with knowledge and understanding
of different table and file formats, and when to apply specific techniques to ensure well
performing solutions
Use of Continuous Integration / Continuous Deployment techniques and principles for
more effective and efficient software development lifecycle.
Experience of writing and evaluating user stories (preferably using Jira) in an Agile
environment
Experience of wider eco-system of modern analytical tools (e.g. Snowflake, Tableau,
Knime, Databricks, Data Mesh Techniques)
Your most important qualities
Drive to succeed and build superior software solutions that delight our users and
stakeholders.
Passion for data engineering and self-improvement, including learning new skills and
technologies.
Good communication and collaboration skills with technology stakeholders.
A drive to make it easier for users to follow Elsevier best practices in integrations.
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Elsevier is 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. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form: https://forms.office.com/r/eVgFxjLmAK , or please contact 1-855-833-5120.
Please read our Candidate Privacy Policy.
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