Data Observability Architect

We are looking for an experienced Data Observability Architect with 10–15 years of experience in Data Engineering/Data Architecture and strong hands-on expertise in Monte Carlo Data Observability. The role involves designing and implementing data observability solutions, proactive monitoring, data quality, lineage, anomaly detection, root cause analysis, and SLA visibility across enterprise data platforms.

Key Responsibilities

• Design the target-state architecture for a Data Observability solution aligned with the enterprise data pipeline framework.
• Implement and integrate Monte Carlo Data Observability with Snowflake, Exadata, SQL Server, dbt, Talend, Informatica, and Denodo.
• Configure proactive monitoring for data freshness, volume anomalies, schema drift, and data quality.
• Enable automated anomaly detection, root cause analysis, impact assessment, and data lineage.
• Integrate observability alerts with ServiceNow and develop operational dashboards for SLA and data-quality visibility.
• Collaborate with data engineering and business teams to establish sustainable observability practices and provide knowledge transfer.

Required Skills

• 10–15 years of Data Engineering / Data Architecture experience
• Hands-on experience with Monte Carlo Data Observability
• Strong experience with Snowflake and enterprise data platforms
• Experience with data quality, lineage, anomaly detection, and monitoring
• Experience with SQL Server, Exadata, dbt, Talend, Informatica, or Denodo

Nice-to-Have Skills

• Python
• AWS / GCP cloud fundamentals
• Utilities / Energy domain experience
• Smart Metering (AMI)
• Grid / SCADA systems
• Fabric Data Engineer Associate (DP-700)
• ITIL v4 Foundation (ITIL4F)

Preferred / Required Certifications

• Monte Carlo Customer Certification 101 – Preferred
• SnowPro Advanced Architect (ARA-C01)
• SnowPro Core (COF-C02)