Sr. Data Platform Engineer

Company Overview Docusign brings agreements to life. Over 1.5 million customers and more than a billion people in over 180 countries use Docusign solutions to accelerate the process of doing business and simplify people’s lives. With intelligent agreement management, Docusign unleashes business‑critical data that is trapped inside of documents. Until now, these were disconnected from business systems of record, costing businesses time, money, and opportunity. Using Docusign’s Intelligent Agreement Management platform, companies can create, commit, and manage agreements with solutions created by the #1 company in e-signature and contract lifecycle management (CLM). What you’ll do The Data and AI Platform Engineer will design, build, and operate our next‑generation data and AI platform, enabling high‑quality analytics, data science, and AI/ML capabilities at scale. Reporting to the Sr. Director, Data Platform and ML Operations, this role serves as a technical expert on Snowflake and AI infrastructure, with a strong focus on production‑grade reliability and performance. You will work closely with data engineers, data scientists, ML/AI engineers, BI developers, and business stakeholders to turn data and AI requirements into robust platforms, pipelines, and services. This position offers the opportunity to shape our data, ML, and AI architecture, influence best practices, and drive innovation across our Data Analytics Organisation. This position is an individual contributor role reporting to the Sr. Director, Data Platform & ML Operations. Responsibilities Design, build, and maintain scalable, secure, high‑performing data and AI platforms using Snowflake and AI infrastructure components (e.g., feature stores, model registries, model serving endpoints) Own and optimize the Snowflake environment (warehouses, databases, schemas, roles, resource monitors) with a focus on performance tuning, cost optimization, and capacity planning for both data and AI workloads Stay current on Snowflake releases, the modern data stack, BI tooling, AI/ML, MLOps, and generative AI best practices and proactively recommend platform improvements Design, build, and operationalize AI capabilities in Snowflake using Snowflake Cortex and native Snowflake AI features to power governed, production‑grade conversational, retrieval‑augmented, and predictive applications Build and operate AI agents and workflows in Snowflake Cortex or similar platforms, integrating tools and context while optimizing prompt patterns to ensure reliable, high‑quality LLM outcomes Contribute to and evolve the overall data, ML, and AI architecture (warehouse, lake/lakehouse, streaming, feature and vector stores, model serving, AI app layers) while establishing and enforcing best practices for data modeling, AI/ML pipeline development, code reviews, testing, deployment, and documentation across the stack Automate infrastructure and deployment using CI/CD and Infrastructure‑as‑Code for data pipelines, ML workflows, and AI/LLM services Architect and manage AWS‑based data and AI infrastructure including S3‑backed data lakes, MWAA/Airflow environments, and supporting services for data ingestion, transformation, and model deployment Implement robust monitoring, logging, and cost‑management practices for AWS data and AI services to ensure platform reliability, security, and efficiency Collaborate with cloud, networking, security, compliance, and infrastructure teams to design resilient, scalable AWS architectures that integrate Snowflake, AI services, and downstream analytics/applications while implementing and maintaining strong data and AI governance (RBAC, masking, encryption, audit logging, responsible AI controls) Partner with data analysts, data scientists, ML/AI engineers, BI developers, and business stakeholders to translate data and AI requirements into scalable, secure technical solutions that deliver actionable insights and business value Job Designation 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. Qualifications Basic Qualifications Bachelor’s or Master’s degree in Computer Science or a related field 8+ years with a Bachelor’s degree or 6+ years of relevant experience with a Master’s degree Experience as a Data Platform Engineer or ML/AI Engineer with significant hands‑on work in Snowflake Administration Experience with SQL and at least one programming language commonly used in data and ML (Python) Experience designing, building, and operating orchestration infrastructure for data pipelines (e.g., Airflow or similar) Experience with core ML lifecycle concepts (data preparation, training, evaluation, deployment, monitoring) and how to support them with data and platform engineering Experience with cloud platforms (e.g., AWS, Azure) and Infrastructure‑as‑Code and CI/CD practices for data/ML workloads Experience working with at least one BI or analytics visualisation tool (e.g., Tableau, Hex, or similar) Preferred Qualifications Deep expertise with Snowflake performance tuning, resource management, and cost optimization for mixed analytics and AI workloads Strong communication and collaboration skills with the ability to work closely with technical and non‑technical stakeholders Strong understanding of data governance and responsible AI principles, including data privacy, security, and model monitoring considerations Experience integrating Snowflake with modern BI and analytics tools such as Tableau including optimizing semantic models and queries for performant, governed self‑service analytics Hands‑on experience building and operating AI agents or agentic workflows using Snowflake Cortex or other agent frameworks and platforms Experience with Snowflake Cortex, including building and managing Cortex agents and leveraging the Snowflake semantic layer to enable AI‑ready, governed analytics experiences Demonstrated experience with prompt engineering, including designing, evaluating, and iterating on prompts for LLM‑powered applications and workflows Experience partnering with data science and ML engineering teams to take models from experimentation to production at scale Hands‑on background with MLOps platforms and tools (e.g., MLflow, Feast, feature stores, model registries, model serving frameworks) Experience implementing real‑time or streaming data pipelines to power low‑latency ML and AI use cases Practical experience with AWS data and analytics services (e.g., S3, MWAA/Airflow, Glue, Lambda, Step Functions, API Gateway) supporting large‑scale data and AI workloads Wage Transparency Pay for this position is based on a number of factors including geographic location and may vary depending on job‑related knowledge, skills, and experience. Based on applicable legislation, the below details pay ranges in the following locations: California: $140,000.00 - $225,075.00 base salary This role is also eligible for the following: Bonus: Sales personnel are eligible for variable incentive pay dependent on their achievement of pre‑established sales goals. Non‑Sales roles are eligible for a company bonus plan, which is calculated as a percentage of eligible wages and dependent on company performance. Stock: This role is eligible to receive Restricted Stock Units (RSUs). Global benefits provide options for the following: Paid Time Off: earned time off, as well as paid company holidays based on region Paid Parental Leave: take up to six months off with your child after birth, adoption or foster care placement Full Health Benefits Plans: options for 100% employer paid and minimum employee contribution health plans from day one of employment Retirement Plans: select retirement and pension programs with potential for employer contributions Learning and Development: options for coaching, online courses and education reimbursements Compassionate Care Leave: paid time off following the loss of a loved one and other life‑changing events States Not Eligible for Employment This position is not eligible for employment in the following states: Alaska, Hawaii, Maine, Mississippi, North Dakota, South Dakota, Vermont, West Virginia and Wyoming. Equal Opportunity Employer It’s important to us that we build a talented team that is as diverse as our customers and where all employees feel a deep sense of belonging and thrive. We encourage great talent who bring a range of perspectives to apply for our open positions. Docusign is an Equal Opportunity Employer and makes hiring decisions based on experience, skill, aptitude and a can‑do approach. We will not discriminate based on race, ethnicity, color, age, sex, religion, national origin, ancestry, pregnancy, sexual orientation, gender identity, gender expression, genetic information, physical or mental disability, registered domestic partner status, caregiver status, marital status, veteran or military status, or any other legally protected category. EEO Know Your Rights poster #J-18808-Ljbffr DocuSign, Inc.