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# Lead Data Engineer

- **Company:** Docusign, Inc.
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $164,700 - $266,000
- **Contract:** Permanent contract
- **Skills:** Computing Platforms, Microsoft Azure, Code Coverage, Databases, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Systems, Python (Programming Language), Operational Data Store, Operational Databases, Kusto Query Language, SQL Databases, Data Processing, Multi-Cloud, Reliability of Systems, Microsoft Fabric, Data Lakes, Data Lineage, Deployment Automation, Data Management, DocuSign, Data Pipelines
- **Published:** November 8, 2026
- **Apply:** https://diversityjobs.com/career/18872996/Lead-Data-Engineer-California-San-Francisco

## About the Role

* 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

## Description

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.
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