Senior Data Engineer
Listed on 2026-08-04
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IT/Tech
Information Security & Data Protection, Data Engineering
Build your future with Sovos.
If you're seeking a career where innovation meets impact, you've come to the right place. As a global leader, Sovos is transforming tax compliance from a business requirement to a force for growth while revolutionizing how businesses navigate the ever-changing regulatory landscape.
At Sovos, we're dedicated to more than just solving compliance challenges -- we're committed to making a positive and lasting difference in everything we do. Our teams operate on the modern edge of digital technology, working not only to solve complex business challenges but also to enrich our personal, professional, and local communities.
Our purpose-built systems provide the tools you need to thrive in a world where governments demand increased visibility, faster reporting and greater control over business processes. Excited about the possibilities? So are we!
The Work You'll Do:At Sovos, we're building a world-class financial data platform to support a global tax compliance leader -- and the Senior Data Engineer is the foundation it all runs on. In this role, you'll own the full pipeline stack: from ingestion through transformation, all the way to the finance-trusted, close-ready outputs that Financial Planning and Analysis (FP&A), Accounting, and leadership rely on to make critical decisions.
You'll design and build the Snowflake architecture and dbt model infrastructure that underpins our topline data chain, and you'll be the person the team counts on when something needs to be fixed before close. This isn't just plumbing -- it's high-visibility, high-ownership engineering work with a direct line to business impact. You'll also play a key role in shaping how AI consumers interact with structured financial data, treating them as first-class stakeholders alongside finance teams.
More specifically, you will:
- Design and build the Snowflake schema and dbt model architecture for the topline data chain:
Billing, Annual Recurring Revenue (ARR), Deferred Revenue, Revenue Recognition (Rev Rec), and Close Pack - Deliver ingestion and transformation models with full test coverage and documentation across all assigned use cases
- Own pipeline reliability through financial close -- monitor, alert on, and recover from failures; serve as the primary on-call escalation point
- Establish data quality standards, dbt testing conventions, and Snowflake governance patterns for the broader team
- Partner with the Analytics Engineer on business-layer model design to ensure technical outputs map accurately to finance requirements
- Extend the dbt model layer to cover operating expenses (OPEX), cost of goods sold (COGS), commissions, and ASC 340-40 capitalized software as scope grows
- Write dbt YAML documentation -- table descriptions, column definitions, and grain statements -- as a first-class production deliverable, recognizing that documentation quality directly determines AI answer accuracy
- Own row-level security and model freshness SLAs for real-time AI queries, treating AI consumers as first-class stakeholders alongside finance
- 5-8 years of experience in data engineering, with a track record of building and maintaining production pipelines and dbt projects at scale
- Advanced SQL skills: CTEs, window functions, LATERAL joins, performance tuning, and complex multi-source financial queries
- Production dbt experience: modular models, tests, documentation, and semantic metadata for both AI and BI consumers
- Snowflake proficiency: roles, warehouses, governance, masking policies, and row-level security -- not just querying, but owning the environment
- Experience supporting financial close cycles, including on-call ownership of pipeline failures; understands what WD1 means and why it matters
- Fluency in the revenue data chain (Billing, ARR, Deferred Revenue, Revenue Recognition, Close Pack) with the ability to engage finance stakeholders directly on data discrepancies
- Strong communication skills: able to explain technical trade-offs to non-technical audiences and write documentation that finance analysts can use to validate outputs
- Preferred:
Experience integrating CRM/ERP systems (Net Suite, Salesforce, or similar)…
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