Certified DataOps Professional — Data Pipeline Automation, Quality & Governance

Certification Overview

The Certified DataOps Professional credential validates your ability to apply DevOps principles to data engineering — version-controlled data pipelines, automated data quality monitoring, schema governance, and data infrastructure as code. This certification demonstrates you can make data pipelines as reliable as application pipelines.

Who Should Enroll

• Data engineers seeking DevOps practices for data pipelines
• Analytics engineers working with dbt, Airflow, or similar tools
• DevOps engineers supporting data platform teams
• Data platform engineers building self-service data infrastructure

Skills Validated

• Data Pipeline CI/CD: dbt, Airflow, Dagster — version-controlled, tested, CI/CD-deployed
• Data Quality Automation: Great Expectations, Soda, dbt tests — freshness, volume, schema, distribution checks
• Schema Governance: Schema registries, compatibility enforcement, breaking change detection
• Data Infrastructure as Code: Terraform for Snowflake, BigQuery, Databricks, Redshift
• Data Observability: Pipeline monitoring, data downtime SLAs, anomaly detection

Assessment Structure

Practical Lab (build a dbt CI/CD pipeline with data quality gates), Capstone Project (DataOps implementation for a multi-source data platform), Scenario-Based Evaluation.

Career Outcomes

Roles: DataOps Engineer, Data Platform Engineer, Analytics Engineer (DataOps), Senior Data Engineer.