RELX is a global provider of information and analytics for professional and business customers across industries.
We help scientists make new discoveries, lawyers win cases, doctors save lives and insurance companies offer customers lower prices. We save taxpayers and consumers money by preventing fraud and help executives forge commercial relationships wit...
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Own specific set or group of data transfers in various capacities including collection setup, data transfer setup, contributor/customer setup, etc.
Interface with other technical personnel or team members to document, interpret, and finalize requirements.
Produce code that is efficient, repeatable, without defects, and adherent to best practices such as naming conventions, encapsulation, etc.
Write and review portions of detailed specifications for the development of data components.
Complete data engineering bug fixes and issues, researching and identifying root causes as appropriate.
Identify opportunities to apply automation or other tools to improve effectiveness or efficiency.
Work closely with other development team members to understand product requirements and translate them into data engineering and/or data management designs.
Innovate process improvements that enable efficient delivery and maintenance and participate in the development processes, coding best practices, and code and project reviews.
Requirements
3+ years’ experience in data management area with a technical competencies demonstrated.
Bachelor’s Degree (Engineering/Computer Science preferred but not required); or equivalent experience required.
Ability to work with data models and strong knowledge of data manipulation languages.
Proficiency in development languages including but not limited to: Java/J2EE, JavaScript, JSP, C/C++, HTML, XML, SQL, Windows, Unix, .Net., HPCC.
Knowledge of AWS, GCP, Azure, or other cloud platform
Experience with relational and NoSQL databases (e.g. Postgres, ElasticSearch/OpenSearch, graph databases such as Neptune or neo4j)
Experience with technologies that power analytics (Spark, Hadoop, Kafka, Docker, Kubernetes) or other distributed computing systems
Knowledge of API development and machine learning deployment
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