Data Engineer III***Hybrid in Horsham, PA

About our Team Lexis Nexis  Legal & Professional, which serves customers in more than 150 countries with 11,800 employees worldwide, is part of RELX , a global provider of information-based analytics and decision tools for professional and business customers. Our company has been a long-time leader in deploying AI and advanced technologies to the legal market to improve productivity and transform the overall business and practice of law, deploying ethical and powerful generative AI solutions with a flexible, multi-model approach that prioritizes using the best model from today’s top model creators for each individual legal use case.

About the Role Conditions of Employment:
*********** You must be a U.S. citizen to apply for this position.

You must successfully pass a background investigation and achieve Public Trust security clearance.

Must be located near the Horsham, PA location for a Hybrid onsite schedule

Requirements

Bachelor’s Degree (Engineering/Computer Science preferred but not required); or equivalent experience required.

Hands-on experience in A zure Synapse Analytics, Azure Databricks, or Hadoop environments.

Minimum 3 years of strong experience developing Python-based Spark code for large-scale data processing.

Solid understanding of Big Data concepts , distributed computing, and data lake-based medallion architecture.

Strong communication and collaboration skills to work with cross-functional teams.

Strong proficiency in Python for data engineering, ETL, and automation tasks.

Good working knowledge of Azure services, including Azure Data Factory (ADF) or Synapse Pipelines, Azure Data Lake Storage (ADLS), and Azure Key Vault/Secrets Management.
• Strong experience with writing SQL Experience working in both Linux and Windows environments for development and deployment.

Solid working knowledge of GIT with Azure Dev Ops (Repos, Pipelines).Experience deploying code to higher environments using CI/CD pipelines & Dev Ops practices in Azure.

Ability to troubleshoot, optimize, and monitor data pipelines in production.

Exposure to Data Warehouses like AWS Redshift, Azure Dedicated SQL Pool, Netezza, etc.

Familiarity with data security, governance, and compliance in cloud environments.

Exposure to monitoring and logging frameworks for data workloads.

Exposure to Microsoft Fabric.

Knowledge of industry best practices (e.g., code coverage).Knowledge of software development methodologies (Agile)
Good documentation skills.

Attention to detail.

Strong oral and written communication skills.

Responsibilities:

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.

Participate in the development processes, coding best practices, and code reviews.

Oversee specific database management ensuring structure and dataflow adheres to department standards.

Utilize various data workflow management and analysis tools.

Maintain a good level of intimacy within a specific data content area.

Participate in process improvement and compliance to successfully and consistently deliver high quality services on time, and to specification, resulting in flexibility to react quickly to changes in priorities or circumstances to meet business needs.

Complete simple data engineering bug fixes and resolve technical issues as necessary.

Work closely with other engineering team members to understand data and translate requirements.

Operate in various development environments (Agile, etc.) while collaborating with key stakeholders.

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