Data Governance Consultant

This is a fully remote position, open to applicants in United States.

📋 Description

• Define, document, and uphold data quality standards, business definitions, and validation criteria for essential reporting and analytics data assets.

• Utilize SQL, dbt, and Snowflake to analyze data, explore quality concerns, validate transformations, and ensure data is ready for business application.

• Collaborate with BI teams to guarantee that dashboards, reports, metrics, and curated datasets are backed by reliable and comprehensible data.

• Oversee routine data quality assessments, detect anomalies, record root causes, and facilitate remediation efforts with data owners and technical teams.

• Maintain metadata, data lineage, business glossaries, and data issue logs to enhance the transparency and usability of data assets.

• Advocate for data governance and stewardship best practices by educating stakeholders on data standards, ownership, and the appropriate use of certified data.

⛳️ Requirements

• Proven experience in data stewardship, data governance, data quality, business intelligence, analytics, or data management.

• Proficient SQL skills with experience in data profiling, business rule validation, discrepancy investigation, and ensuring reporting accuracy.

• Practical experience with dbt, including data testing, documentation, lineage, model reviews, and transformation validation.

• Experience with Snowflake or comparable cloud data warehouse platforms.

• Knowledge of data governance, metadata management, data lineage, data quality dimensions, and data lifecycle principles.

• Advanced SQL capabilities for data analysis, reconciliation, profiling, exception identification, and validating reporting data.

• Familiarity with Snowflake objects, data structures, query performance considerations, and access patterns.

• Experience utilizing dbt tests, source freshness checks, documentation, exposures, and lineage to ensure reliable data delivery.

• Understanding of BI reporting datasets, semantic layers, KPIs, dimensional models, and curated analytics tables.

• Experience in documenting data definitions, transformation logic, ownership, lineage, and known data limitations.

• Strong analytical and problem-solving abilities with the capacity to investigate data issues across source, transformation, and reporting layers.

• Proficient in working with ticketing systems, issue tracking, version control, and collaborative documentation tools.

🏝️ Benefits

• Health insurance

• Professional development opportunities