About our Team

Our mission is to maximize the value of ZI’s comprehensive B2B database through practical application of ML and Generative AI to solving real-world business challenges. To this end, the team has cultivated a powerful fusion of product thinking, ML, language models, and iterative methodologies which work together to deliver a robust suite of data products that inject data-driven intelligence into every facet of ZI. We actively research existing solutions and adapt them to fit our unique requirements, all while leaving ample room for creativity. We collaborate with other data scientists, product managers, ML engineers, subject-matter experts and key business stakeholders to form a cohesive unit dedicated to identifying critical gaps and defining effective approaches to solving the most valuable problems in our business. The result? An impressive array of both experimental and production-ready Data Science products that have a tangible impact on our customer’s ability to generate revenue with their Go-to-Market motion. Embrace the opportunity to join our accomplished team on this transformative journey, where innovation and teamwork thrive, and where your contributions will shape the future of data-driven excellence.

About the Job

As part of our Innovation Data-Science team, you will be working on delivering solutions for a variety of business problems:

• Collaborate with Data Scientists to understand data requirements and translate them into effective data engineering solutions.
• Design, implement, and maintain scalable and efficient data pipelines for data processing, transformation, and analysis.
• Work with large volumes of structured and unstructured data from various sources, ensuring data quality and reliability.
• Optimize and fine-tune data pipelines for performance, throughput, and reliability.
• Develop and maintain ETL (Extract, Transform, Load) processes that enable seamless integration of data into analytical platforms.
• Ensure data security, privacy, and compliance with relevant regulations throughout the data engineering lifecycle.
• Setting up monitoring systems to track data pipeline performance, data quality, and data integrity. Performing data validation to ensure data accuracy and consistency.
• Monitor and troubleshoot data pipeline issues, proactively identifying and resolving bottlenecks or inconsistencies.
• Manage and scale the computing infrastructure required for robust and scalable machine learning workloads.
• Create deployment templates and scripts for model deployment and rollback.
• Explore and implement innovative technologies and tools to enhance data engineering capabilities.
• Document data pipelines, processes, and best practices for knowledge sharing and team collaboration.
• Stay current with industry trends and best practices in data engineering and related technologies.

About You

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.
• 3+ years of experience as a Data Engineer, preferably in a Data Science or analytics-focused environment.
• Proficiency in programming languages such as Python, Java, or Scala.
• Experience with data integration tools and ETL frameworks (e.g., Apache Spark, Apache Beam, Talend, Airflow, dbt).
• Strong SQL skills and experience working with relational and NoSQL databases.
• Familiarity with data warehousing concepts and technologies (e.g., Snowflake, Redshift, BigQuery).
• Understanding of data modeling, schema design, and data normalization/denormalization.
• Knowledge of code version control systems (e.g., Git) and collaborative development practices.
• Excellent problem-solving skills and the ability to work in a fast-paced, dynamic environment.
• Strong communication skills to collaborate with cross-functional teams and translate technical concepts to non-technical stakeholders.
• Preferred:
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge of DevOps practices and tools (e.g. Jenkins, Terraform).
• Previous exposure to Machine Learning frameworks and concepts.
• Contributions to open-source projects or data engineering communities.

The US base salary range for this position is $118,500 to $148,000 + variable compensation + benefits.

Actual compensation offered will be based on factors such as the candidate’s work location, qualifications, skills, experience and/or training. Your recruiter can share more information about the specific salary range for your desired work location during the hiring process.

We want our employees and their families to thrive. In addition to comprehensive benefits, we offer holistic mind, body and lifestyle programs designed for overall well-being. Learn more about ZoomInfo benefits here.

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