Software Engineer, Data Quality

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.