Senior Analytics Engineer

Seismic•,

1d•$103,000 - $140,000

About The Position

Seismic is seeking a Senior Analytics Engineer to join its Corporate Data & Analytics team and own the finance data domain. The role partners with Finance to model, maintain, and scale data assets that support financial reporting, planning, and business decisions. It serves as a technical bridge between Finance stakeholders and the data platform, translating requirements into clean, reliable, well-documented data models. The role also contributes across other business domains and works with data analysts, analytics engineers, and data engineers to build a cohesive, high-quality data layer. It reports to the Manager, Analytics Engineering. The position has ownership of how Finance data is modeled, documented, and trusted across the company. The Senior Analytics Engineer works with Finance stakeholders and technical partners to deliver reusable, tested, and documented data models through cross-functional and agile workflows.

Requirements

At least 5 years of analytics engineering or data analyst experience, including at least 3 years of hands-on dbt Core or dbt Cloud experience building and maintaining production multi-layer model architectures.
Direct experience modeling financial data and working with Finance as a business stakeholder.
Experience partnering directly with business-facing teams on end-to-end analytics projects, from requirements gathering through delivery.
Hands-on experience with a finance SaaS platform such as NetSuite or a similar platform, including modeling financial data and surfacing it from source systems to the reporting layer.
Working knowledge of Salesforce quote-to-cash data structures.
Experience with a cloud data warehouse such as Snowflake, BigQuery, or another data warehouse system.
Expert SQL skills, including complex transformations, window functions, and common table expressions (CTEs).
Experience with Git/GitHub, including branching, pull requests, and code review workflows.
Familiarity with layered dimensional modeling, including separating raw data normalization, business logic, and reporting-ready models.

Nice To Haves

Experience building data models for BI tools such as Tableau, Looker, or Power BI.
Familiarity with agile delivery in a cross-functional engineering environment.
Experience with financial planning tools such as Workday Adaptive Planning.
Experience with integration or automation tools such as Workato.
Background as a data analyst or in a hybrid analyst/engineer role, with an understanding of data consumer needs.

Responsibilities

Collaborate with Finance stakeholders to understand requirements, prioritize work, and deliver data models for financial reporting, revenue recognition, expense tracking, and planning.
Partner with FP&A, Accounting, and Systems teams to build and maintain trusted dbt models for bookings, ARR, and quote-level revenue data, including Salesforce CPQ pricing, discounting, and booking calculations.
Ensure financial metrics reconcile across Finance systems and downstream reporting.
Build and maintain dbt models across the full modeling stack using layered dimensional modeling practices.
Work with data analysts to evaluate reporting requirements and translate business logic into reusable, well-tested data models.
Collaborate with analytics engineers and data engineers on data ingestion, pipeline reliability, and source system changes.
Apply software engineering practices to analytics code, including version control, testing, CI/CD, and documentation.
Maintain clear dbt documentation, including model descriptions, column-level documentation, and lineage.
Participate in project scoping, sprint planning, and cross-functional delivery using agile workflows.