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High brand, generalist Data Engineer role, metro location, broad tooling requirements.
Medium because core data engineering skills transfer across industries despite payments and fraud domain preference.
Medium due to mandatory platform and tooling expertise without explicit years requirement.
Drive data ingestion, aggregation, and processing to enable insights from diverse data sets using platforms like Cloudera, Databricks, and AWS.
Collaborate with Product Managers, Data Science, Platform Strategy, and Technology teams to deliver data solutions generating business value.
Integrate new data assets and innovate through prototypes to enhance data-driven cyber products and actionable business recommendations.
Proficiency in Python including Pandas, Numpy, PySpark, and Impala.
Experience with Hadoop and Databricks Cloud platform for data analysis, development, and testing.
Strong SQL skills and familiarity with data mining, machine learning algorithms, and tools.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in handling large volumes of complex, high-dimensionality data and generating actionable insights at scale.
Able to work effectively across business, analytical, and technical teams to align solution requirements.
Familiar with modern data engineering tools and platforms, including ETL/ELT tools and advanced data modeling techniques.