Senior Data Engineer

Role overview

This is a senior, hands-on data engineering role charged with building the analytics foundation for a high-growth SaaS business from a true greenfield state. The hire will architect and stand up a modern BI data warehouse and lake, own the end-to-end pipeline strategy, and serve as the technical anchor for how internal teams answer their most important questions. The seat carries cross-functional influence across engineering, finance, and product leadership, and is positioned as a foundational hire rather than a maintenance role.

Responsibilities

- Design, implement, and scale a cloud data warehouse and lake from scratch, prioritizing a queryable foundation over interim spreadsheet workarounds - Engineer robust, automated ETL/ELT pipelines that ingest and aggregate data from an Azure-hosted product platform, CRM systems, and external APIs - Produce a written platform recommendation scored on refresh latency, aggregation performance, schema evolution, tenant isolation, three-year total cost of ownership, and migration cost - Establish data governance, quality checks, performance optimization, and source-system semantics to safeguard integrity and query speed - Own freshness, completeness, and reconciliation against a published refresh SLA, with documentation written to a handoff-ready standard - Translate complex data models into plain business language for stakeholders and partner with R&D and Finance on platform selection

Requirements

- 5-7 years of professional experience in data engineering, BI engineering, analytics engineering, or data architecture within a high-growth SaaS environment - Demonstrated ownership of a greenfield data infrastructure initiative end-to-end, including what was chosen, what was rejected, and what would be done differently next time - Deep expertise with modern cloud data warehouses such as Snowflake, Databricks, Azure Synapse, or AWS Redshift, plus data lake architectures - Hands-on experience building complex pipelines with tools like dbt, Apache Airflow, Azure Data Factory, or comparable orchestration frameworks - Advanced proficiency in SQL and query tuning across relational sources such as Azure SQL, SQL Server, and PostgreSQL - Programming fluency in Python, Scala, or C# for data manipulation and automation - Experience extracting and integrating data from enterprise go-to-market tools such as Salesforce, Gainsight, or Marketo

Nice to have

- Prior work integrating non-relational sources like MongoDB into a relational warehouse

Benefits and work setup

- Competitive salary benchmarked to experience, with a full benefits package covering medical, dental, vision, life insurance, 401(k) match, and paid time off - Two office hubs available for in-person collaboration, alongside an emphasis on work/life balance