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Tier-1 brand, metro location, and a popular mid-level data role with common tools increase applicant density.
Core ETL, SQL, and data engineering skills are broadly transferable across industries despite payments context.
Multiple mandatory technical skills and domain experience (ETL, SQL, Spark, Databricks) raise screening strictness.
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Drive and execute data quality validation and pricing monitoring initiatives aligned with compliance requirements.
Develop and maintain data ingestion pipelines, ETL workflows, and dashboards using SQL, cloud platforms, and automation tools.
Collaborate with compliance, data strategy, engineering, and business teams to enable data-driven decision making and ensure data governance adherence.
Bachelor’s degree in Data Science, Computer Science, or related field; Master’s preferred.
Proficiency in SQL and working knowledge of Python, Spark, and Hadoop; experience with ETL and workflow automation.
Experience with cloud-based data platforms (preferably Databricks) and data visualization tools (preferably Power BI).
Work Experience Required: Not explicitly mentioned in the JD.
Strong expertise in data ecosystems, data management, and operational data quality processes.
Experience working cross-functionally with compliance, data strategy, and engineering teams in a complex enterprise environment.
Ability to balance strategic architectural goals with short-term business priorities and drive process improvements.