Senior Data Engineer
Sovos
Senior Data Engineer 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! Don't worry if you don't check all the boxes – apply anyway! We're focused on hiring the right people, not just the "right" resume. It's not about what you've done elsewhere; it's all about what you're capable of doing here. 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 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 US 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 US topline data chain: Billing → ARR → Deferred Revenue → Rev Rec → 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 OPEX, 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 → Rev Rec → 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 (NetSuite, Salesforce, or similar) into a warehouse layer, including ELT patterns, API pagination, and incremental loads
- Preferred: Python for pipeline scripting and orchestration
- Preferred: Cloud infrastructure experience: Azure (App Service, Azure AD, Functions) or AWS; familiarity with auth patterns (JWT, OAuth) and CI/CD fundamentals
- Preferred: Experience with Model Context Protocol (MCP) or similar frameworks for connecting AI agents to structured data
- Preferred: Background in B2B SaaS metrics: ARR, GRR, NRR, churn, and deferred revenue
- Preferred: Familiarity with data governance practices: PII handling, access control, and GDPR basics
- Nice to Have: RAG architecture, hybrid retrieval strategies, or prompt engineering experience
- Nice to Have: MLOps or ML pipeline experience
- Nice to Have: Domain knowledge in compliance, tax technology, or e-invoicing
- Flexible Time-Off
- Comprehensive Health, Dental and Vision benefits
- 401(k) with employee sponsored match
- Bi-Weekly Meeting Free Days
- Mentoring Programs
- Globally recognized Training and Development programs
- Tuition Reimbursement, Time off to Volunteer, Charitable Giving Match, and more!
$105.6k - $132k
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