Lead Data Engineer

Docusign • San Francisco, CA

8h • Hybrid

About The Position

As the Lead Assignment Engine Data Engineer, you will lead the data engineering design of an explainable, configurable engine that converts normalized cloud and operational data into actionable cost attribution. You will define how shared pools—including observability, storage, networking, SQL, and data platforms—are assigned to the products and services that consume them. The role works across data engineering, FinOps, Finance, and platform architecture, requiring strong technical judgment, the ability to turn ambiguous allocation questions into durable data products, and the leadership to establish patterns other engineers can extend.

This is an individual contributor role reporting to the Senior Director, Engineering. The position is hybrid, with at least two days per week in the office and a weekly in-office expectation that may vary by team. The role supports Azure and GCP billing data, with architecture that can extend to additional cloud providers, and may support Microsoft Fabric, Data Lake, Data Factory, and KQL-based consumption patterns where they fit the target architecture. Participation in on-call rotations is required.

Requirements

• 12+ years of professional experience designing and delivering production data platforms or data products, including 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.

Nice To Haves

• FinOps, cloud-cost allocation, showback/chargeback, cost-to-serve, or unit-economics systems experience.
• Multi-cloud billing normalization and FOCUS-aligned data models experience.
• Shared-cost allocation across observability, storage, networking, databases, or data platforms experience.
• Finance-system and revenue-data integration experience.
• Forecasting, anomaly detection, performance-to-cost analytics, or margin reporting experience.
• 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.

Responsibilities

• Build batch and/or streaming pipelines for Azure and GCP billing data, using 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 and completeness checks, and failure-handling patterns.
• Create reusable transformations for 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 data-platform cost efficiency.
• 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.

Benefits

• Company bonus plan for non-sales roles, calculated as a percentage of eligible wages and dependent on company performance.
• Restricted Stock Units (RSUs).
• Paid time off and paid company holidays based on region.
• Up to six months of paid parental leave after birth, adoption, or foster care placement.
• Health benefit plans, including options with 100% employer-paid and minimum employee-contribution plans from day one of employment.
• Retirement and pension programs with potential employer contributions.
• Learning and development options, including coaching, online courses, and education reimbursements.
• Paid compassionate care leave following the loss of a loved one and other life-changing events.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed