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Tier-1 brand, popular Data Engineer role, and metro location increase candidate competition.
Core data engineering skills are highly transferable across industries despite payments domain context.
Multiple mandatory data engineering technologies and domain experience required for lead role.
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Own data ingestion, aggregation, and processing to enable insights from multiple, large data sets using platforms like Cloudera Data Engineering, Databricks, and AWS.
Partner with cross-functional teams (Product, Data Science, Technology) to deliver data solutions that generate business value and support innovative cyber products and services.
Develop proof of concepts and integrate new data assets to enhance existing solutions, focusing on driving business growth through actionable data insights.
Proficient in Python (Pandas, Numpy, PySpark), SQL, and data analysis on Hadoop and Databricks Cloud platforms.
Experience with data ingestion and integration tools; knowledge of ETL/ELT tools preferred (e.g., Apache NiFi, Azure Data Factory).
Strong understanding of data mining, machine learning algorithms, data modeling, and data visualization for business intelligence.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in handling complex, high-volume, high-dimensionality data and delivering scalable, innovative data engineering solutions within a cybersecurity or risk-related domain.
Able to navigate and communicate effectively between business, analytical, and technical stakeholders to translate requirements into data products.
Demonstrates strong operational understanding of analytics tools and cloud-based data platforms, thriving in a fast-paced, deadline-driven environment.