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Data Engineer Lead

2 weeks ago

Cape Town, Western Cape, South Africa RELX Full time

About Us

LexisNexis is a leading provider of legal, regulatory, and business information. We help customers increase productivity and improve decision-making and outcomes.

Our 10,500 experts and innovative tools enable us to shape a better world for our customers and communities.

About the Role

We develop innovative products for data analysis, visualization, and research using AI, machine learning, and data visualization techniques.

This position performs research, design, and data engineering assignments within a specific engineering functional area or product line.

  • Own data transfers in various capacities including collection setup, data transfer setup, contributor/customer setup, etc.
  • Interface with technical personnel to document, interpret, and finalize requirements.
  • Produce efficient code without defects and adhere to best practices such as naming conventions, encapsulation, etc.
  • Write and review specifications for the development of data components.
  • Complete data engineering bug fixes and issues, researching root causes as appropriate.
  • Identify opportunities to apply automation or other tools to improve effectiveness or efficiency.
  • Work closely with development team members to understand product requirements and translate them into data engineering designs.
  • Innovate process improvements that enable efficient delivery and maintenance and participate in coding best practices and code reviews.

Requirements

  • 3+ years' experience in data management with 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 Java/J2EE, JavaScript, JSP, C/C++, HTML, XML, SQL, Windows, Unix, .Net., HPCC.
  • Knowledge of cloud platforms such as AWS, GCP, Azure.
  • Experience with relational and NoSQL databases such as Postgres, ElasticSearch/OpenSearch, graph databases like Neptune or neo4j.
  • Experience with technologies that power analytics such as Spark, Hadoop, Kafka, Docker, Kubernetes.
  • Knowledge of API development and machine learning deployment.