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Job description
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)
Who can apply
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