Data Engineer

Requisition ID  

17744

Country   United States of America Location type   Remote About us  

Korn Ferry is a global organizational consulting firm. We help clients synchronize strategy and talent to drive superior performance. Korn Ferry works with organizations to design their structures, roles, and responsibilities. We help them hire the right people to bring their strategy to life. And we advise them on how to reward, develop, and motivate their people. Our 10,000 colleagues serve clients in more than 50 countries.

Korn Ferry Digital is a scaled product business unit within Korn Ferry that develops and sells our suite of talent products and HR technology, supporting clients across six solution areas:

• Organizational Strategy
• Assessment and Succession
• Talent Acquisition
• Leadership and Professional Development
• Sales and Service
• Total Rewards

Our comprehensive talent suite leverages a combination of proprietary talent IP, talent data, analytics and insights to help customers understand their workforce and existing talent gaps, and deliver targeted talent interventions at scale using HR technology.

Job description  

The Data Engineer role on Korn Ferry’s Digital Product Development team presents an exciting opportunity to work on large-scale data infrastructure projects and contribute to the development and maintenance of our data platform. The ideal candidate will have a strong background in data engineering, data architecture, and cloud technologies. As a Data Engineer, you will collaborate with cross-functional teams including data scientists, analysts, and software engineers to build and optimize data pipelines, data integration processes, and data storage solutions.

**Special note: this role requires a combination of experience on PostgreSQL and Databricks databases. Please only apply if you have experience in both.**

KEY RESPONSIBILITIES

• Design, develop, and maintain data pipelines, ETL/ELT processes, and data integrations to support efficient and reliable data ingestion, transformation, and loading.
• Collaborate with API developers, and other stakeholders to understand data requirements and ensure the availability, reliability, and accuracy of the data.
• Optimize and tune performance of data processes and workflows to ensure efficient data processing and analysis at scale.
• Implement data governance practices, including data quality monitoring, data lineage tracking, and metadata management.
• Work closely with infrastructure and DevOps teams to ensure the scalability, security, and availability of the data platform and data storage systems.
• Continuously evaluate and recommend new technologies, tools, and frameworks to improve the efficiency and effectiveness of data engineering processes.
• Collaborate with software engineers to integrate data engineering solutions with other systems and applications.
• Document and maintain data engineering processes, including data pipeline configurations, job schedules, and monitoring and alerting mechanisms.
• Stay up to date with industry trends and advancements in data engineering, cloud technologies, and data processing frameworks.
• Able to implement and troubleshoot Rest services in Python.

PROFESSIONAL EXPERIENCE/QUALIFICATIONS

• 5+ years of experience in data engineering or a related field, with a solid understanding of cloud platforms and big data technologies.
• Previous experience functioning as a team lead on a data engineering team.
• Strong proficiency in Python or another programming language commonly used in data engineering, such as Java.
• Excellent SQL skills with ability to work with data across different SQL databases including Postgres, Databricks, SQL Server etc. NoSQL databases is a plus
• Knowledge of elastic Search/log stash implementation skills very desirable
• Experience in building and optimizing ETL/ELT processes, data pipelines, and workflows, using tools like Apache Nifi, or Apache Kafka.
• Familiarity with data modeling, data warehousing concepts, and data governance best practices.
• Strong problem-solving and troubleshooting skills, with the ability to identify and resolve data quality and performance issues.
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