Company Overview Docusign brings agreements to life. More than 1.8 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 the Docusign AI-native IAM 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 As the Lead Assignment Engine Data Engineer, you will lead the data engineering design for an explainable, configurable engine that converts normalized cloud and operational data into actionable cost attribution. You will define how shared pools such as observability, storage, networking, SQL, and data platforms are assigned to the products and services that consume them. You will operate at the boundary of data engineering, FinOps, Finance, and platform architecture. The role requires strong technical judgment, the ability to turn ambiguous allocation questions into durable data products, and the leadership to establish patterns that other engineers can extend. This position is an individual contributor role reporting to the Senior Director, Engineering. Responsibility Build batch and/or streaming pipelines for Azure and GCP billing data, with an architecture that can extend to additional cloud providers Normalize provider-specific billing and usage data into a consistent, FOCUS-aligned model Ingest and join resource inventory, tagging, ownership, product, service, and environment metadata Implement reconciliation checks between source billing systems, the normalized warehouse, and downstream reporting datasets Establish data contracts, schemas, lineage, freshness checks, completeness checks, and failure-handling patterns Create reusable transformations that support executive dashboards, product-level cost views, burn-rate reporting, and anomaly detection Build operational visibility for pipeline health, including freshness, latency, volume, schema drift, and failed-record monitoring Partner with platform, FinOps, Finance, and service-owning teams to resolve data-quality gaps and improve attribution coverage Document pipeline behavior, ownership, runbooks, recovery procedures, and known data limitations Improve automation, test coverage, deployment safety, and cost efficiency of the data platform Build or integrate event-driven ingestion patterns so new Cost Management exports trigger processing without manual refreshes Participate in on-call rotations and contribute to improving system reliability and incident response Support Microsoft Fabric, Data Lake, Data Factory, and KQL-based consumption patterns where they fit the target architecture 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. What you bring Basic 12+ years of professional experience designing and delivering production data platforms or data products, including experience leading technical design for complex data systems Experience with SQL and Python or an equivalent data-engineering language Experience with data modeling, ELT/ETL architecture, orchestration, testing, observability, and operational ownership Experience translating business rules into scalable, configurable, and auditable data-processing systems Experience leading technical decisions across multiple teams and stakeholders Preferred FinOps, cloud-cost allocation, showback/chargeback, cost-to-serve, or unit-economics systems Multi-cloud billing normalization and FOCUS-aligned data models Shared-cost allocation across observability, storage, networking, databases, or data platforms Finance-system and revenue-data integration Forecasting, anomaly detection, performance-to-cost analytics, or margin reporting Technical leadership or mentoring responsibility for a data-engineering team Experience designing FinOps data products on Microsoft Fabric or a comparable eventhouse/warehouse architecture Experience with repeatable infrastructure or deployment automation, pre-flight validation, idempotent recovery, and verification reporting Strong communication skills, including the ability to explain data lineage, assumptions, and tradeoffs to technical and non-technical audiences 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: $188,300.00 - $266,000.00 base salary Washington: $164,700.00 - $232,575.00 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 Work Authorization Notice: Please note that we do not provide visa sponsorship or immigration support for this position. Applicants must already be authorized to work in the United States on a full-time, permanent basis without the need for current or future sponsorship. Life at Docusign Working here Docusign is committed to building trust and making the world more agreeable for our employees, customers and the communities in which we live and work. You can count on us to listen, be honest, and try our best to do what’s right, every day. At Docusign, everything is equal. We each have a responsibility to ensure every team member has an equal opportunity to succeed, to be heard, to exchange ideas openly, to build lasting relationships, and to do the work of their life. Best of all, you will be able to feel deep pride in the work you do, because your contribution helps us make the world better than we found it. And for that, you’ll be loved by us, our customers, and the world in which we live. Accommodation Docusign is committed to providing reasonable accommodations for qualified individuals with disabilities in our job application procedures. If you need such an accommodation, or a religious accommodation, during the application process, please contact us at accommodations@docusign.com. If you experience any issues, concerns, or technical difficulties during the application process please get in touch with our Talent organization at taops@docusign.com for assistance. Applicant and Candidate Privacy Notice 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 As the Lead Assignment Engine Data Engineer, you will lead the data engineering design for an explainable, configurable engine that converts normalized cloud and operational data into actionable cost attribution. You will define how shared pools such as observability, storage, networking, SQL, and data platforms are assigned to the products and services that consume them. You will operate at the boundary of data engineering, FinOps, Finance, and platform architecture. The role requires strong technical judgment, the ability to turn ambiguous allocation questions into durable data products, and the leadership to establish patterns that other engineers can extend. This position is an individual contributor role reporting to the Senior Director, Engineering. Responsibility Build batch and/or streaming pipelines for Azure and GCP billing data, with an architecture that can extend to additional cloud providers Normalize provider-specific billing and usage data into a consistent, FOCUS-aligned model Ingest and join resource inventory, tagging, ownership, product, service, and environment metadata Implement reconciliation checks between source billing systems, the normalized warehouse, and downstream reporting datasets Establish data contracts, schemas, lineage, freshness checks, completeness checks, and failure-handling patterns Create reusable transformations that support executive dashboards, product-level cost views, burn-rate reporting, and anomaly detection Build operational visibility for pipeline health, including freshness, latency, volume, schema drift, and failed-record monitoring Partner with platform, FinOps, Finance, and service-owning teams to resolve data-quality gaps and improve attribution coverage Document pipeline behavior, ownership, runbooks, recovery procedures, and known data limitations Improve automation, test coverage, deployment safety, and cost efficiency of the data platform Build or integrate event-driven ingestion patterns so new Cost Management exports trigger processing without manual refreshes Participate in on-call rotations and contribute to improving system reliability and incident response Support Microsoft Fabric, Data Lake, Data Factory, and KQL-based consumption patterns where they fit the target architecture Basic 12+ years of professional experience designing and delivering production data platforms or data products, including experience leading technical design for complex data systems Experience with SQL and Python or an equivalent data-engineering language Experience with data modeling, ELT/ETL architecture, orchestration, testing, observability, and operational ownership Experience translating business rules into scalable, configurable, and auditable data-processing systems Experience leading technical decisions across multiple teams and stakeholders Preferred FinOps, cloud-cost allocation, showback/chargeback, cost-to-serve, or unit-economics systems Multi-cloud billing normalization and FOCUS-aligned data models Shared-cost allocation across observability, storage, networking, databases, or data platforms Finance-system and revenue-data integration Forecasting, anomaly detection, performance-to-cost analytics, or margin reporting Technical leadership or mentoring responsibility for a data-engineering team Experience designing FinOps data products on Microsoft Fabric or a comparable eventhouse/warehouse architecture Experience with repeatable infrastructure or deployment automation, pre-flight validation, idempotent recovery, and verification reporting Strong communication skills, including the ability to explain data lineage, assumptions, and tradeoffs to technical and non-technical audiences
