Data Engineer II

Nextens; United States; Remoto; USD 90.000 - 130.000; Tempo pieno

Descrizione del lavoro

LexisNexis Risk Solutions is seeking a Data Engineer to design, develop, test and support reliable data solutions that ensure high-quality data products for the insurance lifecycle. You will focus on Data Management activities and evolve into broader Data Engineering ownership, collaborating with technical teams and stakeholders to translate requirements into scalable data solutions.

You will contribute to data profiling, validation and quality management, and pursue automation opportunities,

Competenze

• Experience in Data Management, Data Engineering or a related technical data role.
• Strong knowledge of data manipulation, profiling, validation and data quality practices.
• Experience with data models, data requirements and maintainable data solution designs.
• Experience with development technologies such as SQL, Java/J2EE, JavaScript, C/C++, .NET, HTML/XML, HPCC, Windows or Unix.
• Understanding of software engineering practices, including testing, code reviews, maintainability and development methodologies such as Agile or Waterfall.
• Strong analytical and problem-solving skills, with the ability to assess alternatives and recommend appropriate solutions.
• Clear communication skills, attention to detail and an interest in learning and applying new technologies, including AI-assisted engineering and automation

Mansioni

• Own assigned data transfers and components, including collection, transfer and contributor/customer setup, with responsibility for their ongoing maintainability.
• Collaborate with technical teams and stakeholders to understand data and product requirements and translate them into effective data solutions.
• Design, develop, test and maintain efficient, repeatable and maintainable data engineering solutions using established coding and engineering practices.
• Evaluate technical approaches and recommend solutions that balance delivery, data quality, testing and maintainability.
• Perform Data Management activities, including data profiling, validation, quality management and investigation and resolution of data issues.
• Troubleshoot data engineering issues, identify root causes and implement sustainable fixes.
• Identify opportunities for automation, including AI-assisted engineering and intelligent automation, to improve productivity, troubleshooting and delivery.
• Contribute to code reviews, technical specifications, database and workflow management, process improvement and adoption of relevant new technologies.

Conoscenze

Data profiling

Data quality

Data management

SQL

Java/J2EE

JavaScript

C/C++

.NET

Agile/Waterfall

AI-assisted automation

Strumenti

SQL

Java/J2EE

JavaScript

C/C++

HTML/XML

HPCC

Windows

Unix

Descrizione del lavoro

What excites you about designing and delivering reliable data solutions that improve data quality and drive better decisions across the insurance lifecycle?

Are you motivated by solving complex data challenges, working with modern engineering practices and exploring AI-assisted automation to create meaningful business impact?

About the Business

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Insurance vertical, we provide customers with solutions and decision tools that combine public and industry specific content with advanced technology and analytics to assist them in evaluating and predicting risk and enhancing operational efficiency. Our insurance risk solutions help drive better data-driven decisions across the insurance policy lifecycle, all while reducing risk. You can learn more about LexisNexis Risk at https://risk.lexisnexis.com/insurance.

About the Role

As a Data Engineer, you will design, develop, test and support reliable data solutions that enable high-quality data products and services. Initially focused on Data Management activities, you will play a key role in data profiling, validation, quality management and issue resolution while growing into broader Data Engineering ownership.

Working closely with technical teams and business stakeholders, you will translate data requirements into scalable and maintainable solutions, helping to improve data quality, operational efficiency and customer outcomes across our Insurance business.

Responsibilities

• Own assigned data transfers and components, including collection, transfer and contributor/customer setup, with responsibility for their ongoing maintainability.
• Collaborate with technical teams and stakeholders to understand data and product requirements and translate them into effective data solutions.
• Design, develop, test and maintain efficient, repeatable and maintainable data engineering solutions using established coding and engineering practices.
• Evaluate technical approaches and recommend solutions that balance delivery, data quality, testing and maintainability.
• Perform Data Management activities, including data profiling, validation, quality management and investigation and resolution of data issues.
• Troubleshoot data engineering issues, identify root causes and implement sustainable fixes.
• Identify opportunities for automation, including AI-assisted engineering and intelligent automation, to improve productivity, troubleshooting and delivery.
• Contribute to code reviews, technical specifications, database and workflow management, process improvement and adoption of relevant new technologies.

Requirements

• Experience in Data Management, Data Engineering or a related technical data role.
• Strong knowledge of data manipulation, profiling, validation and data quality practices.
• Experience working with data models, data requirements and maintainable data solution designs.
• Experience with relevant development technologies, such as SQL, Java/J2EE, JavaScript, C/C++, .NET, HTML/XML, HPCC, Windows or Unix.
• Understanding of software engineering practices, including testing, code reviews, maintainability and development methodologies such as Agile or Waterfall.
• Strong analytical and problem-solving skills, with the ability to assess alternatives and recommend appropriate solutions.
• Clear communication skills, attention to detail and an interest in learning and applying new technologies, including AI-assisted engineering and automation

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