Data Engineer II

• Partner with stakeholders to define and document data requirements (access, cadence, ownership) and assess feasibility and total cost of ownership (TCO).
• Define data contracts and ownership boundaries with upstream system owners.
• Design and maintain scalable data pipelines that ingest and load data into analytical platforms (e.g., Azure Data Explorer/Kusto).
• Implement data validation and quality checks to meet SLAs for accuracy, completeness, freshness, and reliability.
• Build orchestration and automation for dependable, repeatable data movement.
• Transform and model data (joins, aggregations, enrichment) to power downstream datasets, dashboards, alerts, and agent experiences; contribute through code reviews and shared tooling.
• Operationalize pipelines with monitoring, troubleshooting/runbooks, root-cause analysis, performance/cost optimization, and compliance/governance (classification, tagging, lineage, and access control).

• Master's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 1+ year(s) experience in business analytics, data science, software development, data modeling, or data engineering.

• OR Bachelor's Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 2+ years experience in business analytics, data science, software development, data modeling, or data engineering.
• OR equivalent experience.

Other Requirements: Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings:

• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Preferred Qualifications:

• 5+ years of experience in data engineering or software engineering.
• Experience with Azure data platforms such as Azure Data Explorer (Kusto) or Cosmos DB.
• Experience supporting analytics, reporting, or data science workloads.
• Familiarity with orchestration, monitoring, and alerting for production data systems.
• Strong ownership and operational accountability.
• Experience building and maintaining data pipelines using SQL or programmatic tooling.
• Experience working with cloud-based data platforms.
• Understanding of data quality, validation, and operational reliability concepts.

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