*position summary*
*key responsibilities*
- perform data quality audits, profiling, validation, and cleansing activities across multiple datasets and systems.
- identify data anomalies, inconsistencies, and gaps; investigate issues and drive timely resolution.
- partner with data engineering, analytics, and business teams to define and enforce data quality rules, metrics, and governance standards.
- analyze large datasets using sql and python to diagnose issues and propose remediation steps.
- develop and maintain data quality reports, dashboards, and monitoring processes.
- support data warehouse-related initiatives, ensuring accurate ingestion, transformation, and storage of data.
- contribute to continuous improvement of data quality processes, documentation, and best practices.
- communicate insights, findings, and recommendations effectively to technical and non‐technical stakeholders.
*required skills & qualifications*
- bachelor's degree in computer science, information systems, data analytics, or related field.
- strong hands-on experience with *sql* (complex queries, joins, analytics functions).
- proficiency in *python* for data processing and analysis.
- solid understanding of *data quality concepts*, data governance, metadata, and data lifecycle management.
- strong knowledge of *data warehouse concepts* (dimensions, facts, etl/elt, schemas).
- excellent analytical thinking, problem‐solving, and troubleshooting skills.
- strong communication skills with the ability to present findings clearly.
- demonstrated ability to work collaboratively as a *team player* in cross‐functional environments.
*preferred / nice-to-have skills*
- experience with *snowflake* (warehouse architecture, sql, features such as stages, tasks, streams, tagging).
- familiarity with data quality tools (informatica idq/cdq, talend, great expectations, etc.).
- experience in building automated data validation frameworks.
- experience in building power bi dashboards
*personal attributes*
- detail‐oriented with a passion for clean, reliable data.
- self‐motivated and proactive in identifying and proposing improvements.
ability to manage multiple priorities and deadlines.