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Remote role plus mid-level experience increases applicant pool despite niche data-quality specialization.
Core data engineering skills are transferable but loyalty/CDP and identity-resolution experience create moderate industry specificity.
Explicit 5+ years requirement plus mandatory SQL, Snowflake, Azure, identity-resolution and scripting skills increases filter rigidity.
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Own end-to-end data cleansing and customer profile deduplication using deterministic and probabilistic matching across multiple loyalty platforms.
Develop and maintain automated data quality validation pipelines and reconciliation jobs across platforms like mParticle, Braze, Snowflake, and Azure SQL.
Establish continuous monitoring and observability frameworks including KPIs, dashboards, alerting, and integration validation via REST APIs to ensure data integrity and timely issue resolution.
5+ years experience in data quality engineering, data engineering, or related discipline.
Strong proficiency in SQL (Azure SQL, Snowflake) and scripting/automation using C# (.NET) or Python.
Hands-on experience with REST APIs for data validation and cross-platform reconciliation.
Experience in customer profile deduplication, identity resolution, loyalty or MarTech platforms (mParticle, Braze, Xenial Beanstalk, GiveX).
Experienced in designing and operating cloud-native data quality and observability frameworks within high-volume consumer-facing or loyalty data environments.
Skilled in autonomous work with ability to manage priorities and deliver actionable findings with minimal oversight.
Familiar with identity resolution techniques, data privacy regulations (CCPA, GDPR), and consent management in retail or QSR contexts.