Compensation Overview

ZoomInfo’s strength is its extensive and accurate company and contacts database. The objective of the Identity resolution graph is to identify all the individual sources of information spread across numerous data sources in ZI as well as data gaps that need to be filled to create one of the most powerful B2B Identity Graphs.

For MarketingOS, having a robust identity graph would make our Advertising, Websights and Intent products more sticky and valuable to our customers, and opens up opportunities in the realm of personalization and monetization. A full range of identifiers associated with both devices and people will be inventoried and considered for inclusion in the identity resolution service for both visitor identification and ad use cases. From an Advertising perspective, Identity graph will be used to identify (and map all the identities) and activate marketing activities on different platforms (display, social, email, platforms, etc), reporting and take attribution across website engagement (Websights) activities, to CRM conversion(closed /won deals)

What you’ll do :

• Architect and develop large-scale, distributed data processing pipelines using technologies like Apache Spark, Apache Beam, and Apache Airflow for orchestration.
• Design and implement efficient data ingestion, transformation, and storage solutions for structured and unstructured data.
• Partner closely with Engineering Leaders, Architects, and Product Managers to understand business requirements and provide technical solutions within a larger roadmap.
• Build and optimize real-time and batch data processing systems, ensuring high availability, fault tolerance, and scalability.
• Collaborate with data engineers, analysts, and scientists to understand business requirements and translate them into technical solutions.
• Implement best practices for data governance, data quality, and data security across the entire data lifecycle.
• Mentor and guide junior engineers, fostering a culture of continuous learning and knowledge sharing.
• Stay up-to-date with the latest trends, technologies, and industry best practices in the big data and data engineering domains.
• Participate in code reviews, design discussions, and technical decision-making processes.
• Contribute to the development and maintenance of CI/CD pipelines, ensuring efficient and reliable deployments.
• Collaborate with cross-functional teams to ensure the successful delivery of projects and initiatives.

What you’ll bring:

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• Minimum of 10 years of experience in backend software development, with a strong focus on data engineering and big data technologies.
• Proven expertise in Apache Spark, Apache Beam, and Airflow, with a deep understanding of distributed computing and data processing frameworks.
• Proficient in Java, Scala and SQL, with the ability to write clean, maintainable, and efficient code.
• Proven experience building enterprise-grade software in a cloud-native environment (GCP or AWS) using cloud services such as GCS/S3, Dataflow/Glue, Dataproc/EMR, Cloud Function/Lambda, BigQuery/Athena, BigTable/Dynamo
• Experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes).
• Experience in stream / data processing technologies like Kafka, Spark, Google BigQuery, Google Dataflow, HBase
• Familiarity designing CI/CD pipelines with Jenkins, Github Actions, or similar tools
• Experience with SQL, particularly performance optimization
• Experience with Graph and Vector database or processing frameworks
• Strong knowledge of data modeling, data warehousing, and data integration best practices.
• Familiarity with streaming data processing, real-time analytics, and machine learning pipelines.
• Excellent problem-solving, analytical, and critical thinking skills.
• Strong communication and collaboration skills, with the ability to work effectively in a team environment.
• Experience in mentoring and leading technical teams.

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