Spendflo is a fast-growing Series A startup helping companies streamline how they procure, manage, and optimize their software and services. Backed by top-tier investors, we’re building the most intelligent, automated platform for procurement operations.

We are now looking for a Senior Data Engineer to design, build, and scale our data infrastructure. You’ll be the backbone of all data movement at Spendflo — from ingestion to transformation to reporting.

What You’ll Do:

• Design, implement, and own the end-to-end data architecture at Spendflo
  
• Build and maintain robust, scalable ETL/ELT pipelines across multiple sources and systems
  
• Develop and optimize data models for analytics, reporting, and product needs
  
• Own the reporting layer and work with PMs, analysts, and leadership to deliver actionable data
  
• Ensure data quality, consistency, and lineage through validation and monitoring
  
• Collaborate with engineering, product, and data science teams to build seamless data flows
  
• Optimize data storage and query performance for scale and speed
  
• Own documentation for pipelines, models, and data flows
  
• Stay current with the latest data tools and bring in the right technologies
  
• Mentor junior data engineers and help establish data best practices
  

Required Qualifications:

• 5+ years of experience as a data engineer, preferably in a product/startup environment
  
• Strong expertise in building ETL/ELT pipelines using modern frameworks (e.g., Dagster, dbt, Airflow)
  
• Deep knowledge of data modeling (star/snowflake schemas, denormalization, dimensional modeling)
  
• Hands-on with SQL (advanced queries, performance tuning, window functions, etc.)
  
• Experience with cloud data warehouses like Redshift, BigQuery, Snowflake, or similar
  
• Comfortable working with cloud platforms (AWS/GCP/Azure) and tools like S3, Lambda, etc.
  
• Exposure to BI tools like Looker, Power BI, Tableau, or equivalent
  
• Strong debugging and performance tuning skills
  
• Excellent communication and documentation skills
  

Preferred Qualifications:

• Built or managed large-scale, cloud-native data pipelines
  
• Experience with real-time or stream processing (Kafka, Kinesis, etc.)
  
• Understanding of data governance, privacy, and security best practices
  
• Exposure to machine learning pipelines or collaboration with data science teams
  
• Startup experience — able to handle ambiguity, fast pace, and end-to-end ownership