Job Description:

• Coordinate with product managers and analytics leads during the design and rollout of new Snowflake instances, ensuring each instance meets product-specific and organizational requirements.
• Evaluate business needs and recommend optimal schema designs and data models in Snowflake, in partnership with data engineers and analytics stakeholders.
• Develop and maintain automated pipelines for ingesting, transforming, and validating data from Segment into Snowflake.
• Monitor data pipelines for latency, errors, and data quality issues, responding swiftly to resolve problems and minimize downtime.
• Document setup processes, data flows, and schema definitions to ensure ongoing maintainability and knowledge sharing across teams.
• Stay current on developments in Segment and Snowflake platforms, exploring pilot programs or beta features that could provide analytic advantages.
• Propose and implement new processes to streamline data onboarding for future products, reducing manual effort and increasing reliability.
• Participate in code reviews and contribute to the documentation and refinement of engineering standards related to data integration.
• Communicate findings, risks, and opportunities clearly to both technical and non-technical stakeholders.
• Technical Expertise: Demonstrated experience setting up and managing Snowflake data warehouse environments, including user roles, security, and advanced data modeling.
• Segment Mastery: Familiarity with Segment (or similar CDP tools), including source and destination setup, event tracking, and feature utilization to ensure high data fidelity.
• Data Engineering Fundamentals: Proficiency in SQL, data transformation, and ETL pipeline management. Understanding of data quality best practices and troubleshooting methodologies.
• Collaboration & Communication: Proven ability to collaborate with remote engineers and cross-functional teams, and to communicate complex technical concepts with clarity and confidence.
• Documentation & Process: Strong skills in documenting procedures, data schemas, and integration standards for a technical audience.
• Project Management: Organized and detail-oriented, able to manage multiple parallel product launches and integration tasks efficiently.