Senior Data Quality Analyst

Breakthru Beverage Group•Washington, DC

1d•$96,000 - $110,000•Hybrid

About The Position

Breakthru Beverage Group (BBG) is on an exciting journey to modernize our enterprise data ecosystem and unlock the full potential of data and AI to drive growth, efficiency, and innovation across our business. As part of our enterprise-wide Data & AI transformation, we are building a trusted, governed, and AI-ready data foundation. To support this vision, we are seeking a Senior Data Quality Analyst - a highly skilled and hands-on data professional who will help design, implement, and operationalize BBG’s enterprise data quality and observability capabilities. Reporting to the Sr. Manager, Data Quality, you will work closely with data engineers, stewards, and business partners to monitor and improve data accuracy, completeness, and consistency across critical data domains. This role is ideal for someone who is technically strong in SQL and analytics, detail-oriented, and passionate about data trust and reliability.

Requirements

Bachelor’s degree in computer science, information systems, data management, or a related field.
5+ years of hands-on experience in data analysis, data quality, or data management roles.
Advanced excel skills.
Strong SQL skills with proven ability to perform data profiling, cleansing, and validation across large datasets.
Experience with modern DQ and observability tools such as Monte Carlo, Great Expectations, Soda, or Datafold.
Familiarity with AWS data services, Snowflake or other cloud-native data platforms.
Solid understanding of data integration, data pipelines, and ETL processes.
Excellent problem-solving and analytical skills, with strong attention to detail.
Strong collaboration and stakeholder management skills, with the ability to work effectively across data engineering, governance, and business teams.
Strong communication skills, with the ability to translate technical data findings into actionable business insights.

Nice To Haves

Experience working with data governance and catalog platforms (e.g., Atlan, Collibra, Alation, Informatica) to maintain business glossaries, data lineage, and the linkage between data quality rules and governed data elements.
Experience defining and operationalizing data quality SLAs, data contracts, and stewardship workflows, including partnering with data owners on issue escalation, remediation accountability, and performance reporting.
Familiarity with industry data governance frameworks such as DAMA-DMBOK or EDM Council DCAM; CDMP or similar data management certification a plus.
Working knowledge of data observability concepts (e.g., schema drift, freshness, completeness).
Understanding of master data management (MDM) and metadata-driven data governance principles.
Experience working with SAP (MDG, ECC, or S/4HANA) or other ERP systems in a data management context.

Responsibilities

Develop, implement, and maintain data validation, profiling, and reconciliation routines across multiple data sources using SQL, Python, and modern DQ tools (e.g., Monte Carlo, Great Expectations, Soda, Datafold).
Build and maintain data quality dashboards and scorecards to track key metrics and trends.
Perform root-cause analysis and partner with engineering and stewardship teams to remediate data issues.
Document data quality rules, thresholds, and exception workflows for ongoing monitoring.
Support the configuration and integration of data quality and observability tools with BBG’s Snowflake-on-AWS Datahub.
Collaborate with Data Engineering to embed quality checks directly into ingestion and curation pipelines (via dbt, Airflow, or similar frameworks).
Assist in defining and operationalizing alerting and incident management processes for data anomalies.
Partner with the Data Governance and Stewardship teams to ensure alignment with master data management (MDM) and data governance standards.
Support the rollout of data quality SLAs and ensure that business data owners have clear visibility into data quality performance.
Contribute to the development and documentation of standard operating procedures (SOPs) for data quality and remediation processes.
Identify opportunities to automate and streamline data quality checks and issue resolution processes.
Provide input into continuous improvement of the enterprise DQ framework, tools, and methods.
Support data literacy initiatives by helping business and technical users understand data quality metrics and their impact.
Other duties, as assigned by the jobholder’s supervisor, may also be required.