Data Engineer

Responsibility

• Develop and run LLM-integrated pipelines using Claude, Glean, Gemini, Snowflake Cortex and enterprise copilots
• Define prompt engineering patterns, evaluation methods, and guardrails for production AI applications
• Translate business problems into data + AI solutions that deliver clear, actionable business insights
• Design robust data architectures spanning batch, streaming, and AI inference layers
• Build Snowflake-based pipelines using Python, dbt, and Airflow for analytics and AI workloads
• Implement and maintain data ingestion and reverse-ETL using Fivetran and Hightouch
• Manage AWS infrastructure (S3, EC2, IAM, Lambda, Step Functions, Glue) for data and AI platforms
• Enforce data privacy, governance, and compliance, including PII controls in Snowflake and AWS
• Maintain clear documentation for data platforms, AI systems, and architecture
• Troubleshoot and resolve data and AI issues, driving root-cause fixes
• Deliver work using Agile/Scrum, acting as a strong team player and mentor
• Hybrid: Employee divides their time between in-office and remote work. Access to an office location is required. (Frequency: Minimum 2 days per week; may vary by team but will be weekly in-office expectation)
• Positions at Docusign are assigned a job designation of either In Office, Hybrid or Remote and are specific to the role/job. Preferred job designations are not guaranteed when changing positions within Docusign. Docusign reserves the right to change a position's job designation depending on business needs and as permitted by local law.

Basic