Data Observability Architect: Data Quality & Lineage Leader

Veriipro; Richmond (VA); On-site; USD 140,000 - 210,000; Full time

Job summary

Veriipro is seeking an experienced Data Observability Architect with 10–15 years in Data Engineering and Data Architecture. The role focuses on designing and implementing data observability solutions, proactive monitoring, data quality, lineage, and SLA visibility across enterprise data platforms.

Key responsibilities include integrating Monte Carlo Observability with Snowflake, SQL Server, and other tools, configuring monitoring for data freshness and anomalies, enabling root cause analysis,

Qualifications

• 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.

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 dashboards for SLA and data-quality visibility.
• Collaborate with data engineering and business teams to establish observability practices and transfer knowledge.

Skills

Data architecture

Data engineering

Data observability

Monitoring

Root cause analysis

Tools

Monte Carlo Data Observability

Snowflake

SQL Server

Exadata

dbt

Talend

Informatica

Denodo

ServiceNow

Job description

Veriipro is seeking an experienced Data Observability Architect with 10–15 years in Data Engineering and Data Architecture. The role focuses on designing and implementing data observability solutions, proactive monitoring, data quality, lineage, and SLA visibility across enterprise data platforms.

Key responsibilities include integrating Monte Carlo Observability with Snowflake, SQL Server, and other tools, configuring monitoring for data freshness and anomalies, enabling root cause analysis,