ZoomInfo

ZoomInfo

ZoomInfo provides a comprehensive B2B database that offers accurate and actionable contact and company intelligence, enabling sales and marketing teams to enhance their campaigns and improve prospecting efforts through access to direct dial phone numbe...

Professional Services
1K-5K
Founded 2000

Description

  • Design, develop, and maintain high-performance data pipelines using Airflow, DBT, and Python.
  • Architect and optimize the company’s Snowflake-based data warehouse and lakehouse.
  • Integrate structured and unstructured data sources, including web data and third-party APIs, into the data ecosystem.
  • Implement and enforce Model Context Protocol (MCP) or similar architectures for LLM-powered products, including RAG and advanced search.
  • Collaborate with ML engineers, data scientists, and product managers to deliver scalable data solutions.
  • Define, monitor, and enforce data quality SLAs, including data accuracy and lineage.
  • Mentor junior engineers and promote best practices in code quality, data architecture, and operational excellence.
  • Participate in architectural decisions and long-term strategy for enterprise data infrastructure, with attention to cost, performance, and reliability.

Requirements

  • 8+ years of progressive experience in data engineering with leadership and impact.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • Expert-level SQL for performant, scalable queries and transformations on large datasets.
  • Strong Python programming skills with experience in distributed computing, data manipulation, and robust API development.
  • Production experience with large-scale batch and streaming data processing.
  • Hands-on experience with DBT for data modeling and transformations.
  • Deep knowledge of Snowflake data warehouse design, optimization, and cost modeling.
  • Experience implementing Model Context Protocol (MCP) or similar architectures for structured and unstructured data in LLM-powered systems.
  • Strong understanding of data architecture, including data lakes, event-driven architectures such as Kafka, ETL/ELT, and data mesh.
  • Proficiency with cloud platforms such as GCP and/or AWS and infrastructure as code tools such as Terraform.
  • Familiarity with LLMOps, LangChain, or RAG pipelines, preferred.
  • Experience with embedding models or NER pipelines, preferred.
  • Knowledge of data cataloging tools such as OpenLineage and lineage tracking, preferred.
  • Familiarity with distributed systems and databases such as DynamoDB and Flink, preferred.

Benefits

  • Remote work eligibility, indicated by the #LI-REMOTE designation.
  • Opportunity to work on AI-ready, LLM-powered data products at a global Go-To-Market intelligence platform.
  • A fast-paced, ambitious culture that emphasizes impact and collaboration.
  • Exposure to advanced tools and modern data stack technologies in a core engineering team.
  • Equal employment opportunity and commitment to an inclusive hiring process.

Interested in this position?

Apply directly on the company website

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