Data Engineer – AWS (Data Observability)

Posted Yesterday
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Indianapolis, IN, USA
In-Office
Mid level
Artificial Intelligence • Software • Consulting • Automation
The Role
Build and maintain observability across enterprise data pipelines, including data quality checks, freshness, volume, schema monitoring, alerting, incident triage, root cause analysis, SLA management, and runbooks. Configure tools such as Monte Carlo, Great Expectations, CloudWatch, and Datadog to improve pipeline reliability and data trust.
Summary Generated by Built In

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Implement monitoring and observability across enterprise data pipelines to ensure reliability and data trust.

  • Build data quality checks, freshness/volume/schema monitoring and alerting
  • Set up observability tooling (e.g., Monte Carlo, Great Expectations, CloudWatch, Datadog)
  • Perform incident triage and root cause analysis; maintain SLAs and runbooks

Requirements
  • Must have: 4+ yrs, AWS (Glue, S3, Lambda, Redshift, CloudWatch), Python, SQL, data quality frameworks

Skills Required

  • 4+ years of professional experience
  • Experience with AWS Glue, S3, Lambda, Redshift, and CloudWatch
  • Proficiency in Python
  • Proficiency in SQL
  • Experience with data quality frameworks
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The Company
HQ: Indianapolis, IN
96 Employees
Year Founded: 2015

What We Do

RADcube is a technology consulting and software development firm founded in 2015 and headquartered in Carmel, Indiana. It helps organizations turn enterprise ideas into practical innovations through digital transformation, custom software, data analytics, artificial intelligence, cloud computing, cybersecurity, and intelligent automation. The company serves healthcare, finance, government, and manufacturing clients, combining human-centric delivery with responsible, accountable technology solutions designed to produce measurable business outcomes.

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