Software Engineer, Data Quality

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Software Engineer, Data Quality based in United States.

This role offers the opportunity to build the systems that ensure critical financial and cloud-cost data is accurate, reliable, and customer-ready.

You will work across AWS, Microsoft Azure, and Google Cloud, developing deep expertise in how each provider structures and reports billing data.

Your work will directly protect customers from incorrect financial insights and help them make better infrastructure investment decisions.

You will design automated validation, reconciliation, anomaly detection, and testing capabilities across a broad product surface.

The environment is highly technical, automation-focused, and collaborative, with close interaction across engineering, sales, and customer success.

You will investigate complex data issues, solve them at their root, and create durable controls to prevent them from recurring.

This is an ideal opportunity for an engineer who values precision, enjoys solving data problems, and prefers building automation over repeating manual checks.

Accountabilities:

• Develop deep expertise in the product’s data model and document how AWS, Azure, and Google Cloud represent billing and financial data differently.
• Build automated data validation, reconciliation, and anomaly-detection systems to identify issues before they affect customers.
• Design and maintain reliable workflows using Argo or comparable orchestration technologies to execute automated data-quality checks.
• Investigate data-quality issues through root-cause analysis, implement corrective solutions, and create automated safeguards to prevent recurrence.
• Replace manual pre-demo data checks with durable, scalable automated coverage.
• Expand test automation across critical product and data surfaces to improve reliability and confidence in customer-facing outputs.
• Partner with sales and customer success teams to investigate live data questions and diagnose issues as they arise.
• Apply AI-powered development and analysis tools thoughtfully to accelerate investigation, generate checks, and improve anomaly triage.
• Contribute to data pipelines, ETL processes, and quality controls that make financial and cloud-cost information dependable at scale.
• Continuously identify opportunities to strengthen data integrity, test coverage, automation, and operational reliability.

Requirements:

• 3+ years of software engineering or data engineering experience, or equivalent hands-on experience building and shipping production-quality code.
• Strong attention to detail and a genuine commitment to data accuracy, particularly when data informs financial or customer decisions.
• Strong SQL skills for data transformation, analysis, validation, and reconciliation.
• Comfort with scripting and programming; Python is preferred, though strong engineers with experience in another programming language who are willing to learn Python are encouraged to apply.
• A demonstrated preference for automating recurring checks and processes rather than relying on repetitive manual validation.
• Strong analytical and problem-solving abilities, with the ability to investigate data discrepancies and identify underlying causes.
• Interest in developing deep expertise in the billing and data models used by AWS, Azure, and Google Cloud.
• Comfortable using AI-assisted engineering and data tools with sound judgment to increase productivity and test coverage.
• Experience with cloud billing, FinOps, or other financial-data domains is a plus.
• Familiarity with data-quality frameworks such as dbt tests, Great Expectations, or Soda is desirable.
• Experience with workflow orchestration tools such as Argo, Airflow, or Dagster and with data pipelines or ETL is advantageous.
• Experience with test automation and CI for data or application environments is a plus.
• Strong communication and collaboration skills, particularly when working with cross-functional teams on customer-facing data issues.

Benefits:

• Competitive salary and equity package.
• Comprehensive medical, dental, and vision coverage.
• 401(k) retirement plan.
• Flexible paid time off.
• Company holidays.
• Remote-first working environment.
• Opportunity to work on a growing FinTech platform at the intersection of cloud infrastructure, data, and financial technology.
• Opportunity to develop specialized expertise in cloud billing across AWS, Azure, and Google Cloud.
• High-impact engineering environment where data quality directly influences customer financial decisions.
  • Develop deep expertise in the product’s data model and document how AWS, Azure, and Google Cloud represent billing and financial data differently.
  • Build automated data validation, reconciliation, and anomaly-detection systems to identify issues before they affect customers.
  • Design and maintain reliable workflows using Argo or comparable orchestration technologies to execute automated data-quality checks.
  • Investigate data-quality issues through root-cause analysis, implement corrective solutions, and create automated safeguards to prevent recurrence.
  • Replace manual pre-demo data checks with durable, scalable automated coverage.
  • Expand test automation across critical product and data surfaces to improve reliability and confidence in customer-facing outputs.
  • Partner with sales and customer success teams to investigate live data questions and diagnose issues as they arise.
  • Apply AI-powered development and analysis tools thoughtfully to accelerate investigation, generate checks, and improve anomaly triage.
  • Contribute to data pipelines, ETL processes, and quality controls that make financial and cloud-cost information dependable at scale.
  • Continuously identify opportunities to strengthen data integrity, test coverage, automation, and operational reliability.

  Requirements:

  • 3+ years of software engineering or data engineering experience, or equivalent hands-on experience building and shipping production-quality code.
  • Strong attention to detail and a genuine commitment to data accuracy, particularly when data informs financial or customer decisions.
  • Strong SQL skills for data transformation, analysis, validation, and reconciliation.
  • Comfort with scripting and programming; Python is preferred, though strong engineers with experience in another programming language who are willing to learn Python are encouraged to apply.
  • A demonstrated preference for automating recurring checks and processes rather than relying on repetitive manual validation.
  • Strong analytical and problem-solving abilities, with the ability to investigate data discrepancies and identify underlying causes.
  • Interest in developing deep expertise in the billing and data models used by AWS, Azure, and Google Cloud.
  • Comfortable using AI-assisted engineering and data tools with sound judgment to increase productivity and test coverage.
  • Experience with cloud billing, FinOps, or other financial-data domains is a plus.
  • Familiarity with data-quality frameworks such as dbt tests, Great Expectations, or Soda is desirable.
  • Experience with workflow orchestration tools such as Argo, Airflow, or Dagster and with data pipelines or ETL is advantageous.
  • Experience with test automation and CI for data or application environments is a plus.
  • Strong communication and collaboration skills, particularly when working with cross-functional teams on customer-facing data issues.

  Benefits:

  • Competitive salary and equity package.
  • Comprehensive medical, dental, and vision coverage.
  • 401(k) retirement plan.
  • Flexible paid time off.
  • Company holidays.
  • Remote-first working environment.
  • Opportunity to work on a growing FinTech platform at the intersection of cloud infrastructure, data, and financial technology.
  • Opportunity to develop specialized expertise in cloud billing across AWS, Azure, and Google Cloud.
  • High-impact engineering environment where data quality directly influences customer financial decisions.