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Archera Verified
Cloud Computing, FinOps, AI/ML, Software Development

Software Engineer, Data Quality

RemoteRemoteFull TimePosted 2 months ago

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Required skills

  • data validation
  • reconciliation
  • anomaly detection
  • SQL
  • scripting
  • AWS billing
  • Azure billing
  • Google Cloud billing
  • data quality

Nice to have

  • Python
  • Argo
  • Airflow
  • Dagster
  • dbt tests
  • Great Expectations

Role summary

Archera is seeking a Software Engineer focused on Data Quality to build automated validation, reconciliation, and anomaly detection systems for their FinTech platform. This role involves deep dives into AWS, Azure, and Google Cloud billing data formats to ensure accuracy and prevent issues from reaching customers. The engineer will automate manual checks, investigate root causes of data quality problems, and leverage AI tooling. The ideal candidate has 3+ years of software or data engineering experience, strong SQL fluency, and a preference for automation. Experience with Python, workflow orchestration, test automation, cloud billing, or FinOps is a plus.

Software Engineer, Data Quality

Company Overview

Archera empowers organizations of all sizes to optimize their cloud costs through unique, short-term, insured commitments. Thousands of customers rely on Archera's innovative FinTech solutions to increase their cloud ROI while accelerating revenue objectives and service agility.

Archera's unique cloud rate insurance products and free FinOps platform enable teams to accurately predict and plan infrastructure growth, maximize commitment-based savings, and hedge against market demands and evolving cloud service provider offerings. Archera works closely with AWS, Microsoft Azure, and Google Cloud, along with a broad partner ecosystem, to help customers execute financially prudent cloud strategies.

Position Overview

Customers commit real money based on the numbers Archera shows them, so a wrong number is not a broken dashboard — it is a wrong financial decision. Getting it right is genuinely hard: our product spans a large surface area, and AWS, Azure, and Google Cloud each represent billing in a different format. As a Software Engineer focused on data quality, you will build the automated validation, reconciliation, and anomaly detection that keeps problems from ever reaching a customer, and you will become one of the few engineers anywhere who knows how all three providers really model their billing data.

Key Responsibilities

  • Go deep on the product's data model and on how AWS, Azure, and Google Cloud each format billing differently, documenting what you find rigorously.
  • Build automated data validation, reconciliation, and anomaly detection, including the workflows (Argo or equivalent) that run the checks.
  • Investigate data-quality problems to root cause, fix them, and automate the check that prevents a repeat.
  • Replace the manual data checks the team runs before customer demos with durable, automated coverage.
  • Extend test automation to critical product surfaces.
  • Work with sales and customer success on live data questions, diagnosing and resolving issues as they surface.
  • Use AI tooling to accelerate investigation, check generation, and anomaly triage.

    • Qualifications

  • 3+ years of software or data engineering experience, or equivalent hands-on experience building and shipping code.
  • Strong attention to detail — you notice the number that is subtly wrong, and you care because someone is budgeting against it.
  • SQL fluency for transformation and reconciliation, plus comfort scripting. Python is preferred; a strong engineer who knows SQL and another language and will pick up Python works well here.
  • A preference for automating a check rather than repeating it.
  • Interest in becoming the definitive expert on how three cloud providers each represent billing — knowledge very few engineers have.
  • Comfort with AI tooling, used with judgment, to raise coverage and move faster.

    • Nice-to-Haves

  • Cloud billing across AWS, Azure, or Google Cloud, FinOps, or other financial-data domains.
  • Data-quality frameworks such as dbt tests, Great Expectations, or Soda.
  • Workflow orchestration (Argo, Airflow, Dagster) and data pipeline or ETL experience.
  • Test automation and CI for data or application surfaces.
  • Experience making data trustworthy for customer-facing or revenue-critical use.

    • Benefits

  • Competitive salary and equity package
  • Comprehensive medical, dental, and vision coverage
  • 401(k) plan
  • Flexible PTO and company holidays
  • Remote-first culture
  • Opportunity to shape and scale a category-defining FinTech platform
    • Ready to apply?
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