Staff Data Engineer
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The role
Lead the design, enhancement, and delivery of next-generation fraud detection data solutions in an agile environment.
Translate business problems into technical data problems and ensure key drivers are captured in collaboration with product stakeholders.
Drive end-to-end development, delivering high-quality, scalable ETL/ELT pipelines with strong data quality and anomaly detection.
Collaborate across functions (Product Managers, Architects, Analysts, Developers, Project Managers) to implement data-driven solutions and enable self-serve data tooling for data scientists.
Establish and maintain robust data engineering processes, governance, and infrastructure; manage projects to meet timelines and budget.
Requires hands-on experience with Hadoop, Spark, NoSQL, SQL, Python, and Agile CI/CD in a hybrid Austin setting.
Translate business problems into technical data problems and ensure key drivers are captured in collaboration with product stakeholders.
Drive end-to-end development, delivering high-quality, scalable ETL/ELT pipelines with strong data quality and anomaly detection.
Collaborate across functions (Product Managers, Architects, Analysts, Developers, Project Managers) to implement data-driven solutions and enable self-serve data tooling for data scientists.
Establish and maintain robust data engineering processes, governance, and infrastructure; manage projects to meet timelines and budget.
Requires hands-on experience with Hadoop, Spark, NoSQL, SQL, Python, and Agile CI/CD in a hybrid Austin setting.
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Remote workPartial
CityAustin, United States