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Tier-1 employer, popular data-engineer role, metro location and broad skillset create high competition.
Core data engineering skills are highly transferable across industries despite payments domain context.
Strong mandatory tech and platform requirements (Hadoop, Databricks, PySpark, SQL) increase filtering stringency.
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Drive data ingestion, aggregation, and processing utilizing platforms such as Cloudera Data Engineering, Cloudera AI, Databricks, and AWS to enable actionable insights.
Partner cross-functionally with Product Managers, Data Science, Platform Strategy, and Technology teams to deliver data solutions that create business value.
Unify and curate data assets to provide a single unified view from multiple sources, supporting development of innovative data-driven cyber products, services, and actionable recommendations.
Proficiency with Python (Pandas, Numpy, PySpark), Impala, and strong SQL skills.
Experience with Hadoop and Databricks Cloud platform for data analysis, development, and testing.
Work Experience Required: Not explicitly mentioned in the JD.
Familiarity with data integration tools (ETL/ELT) such as Apache NiFi, Azure Data Factory, Pentaho, or Talend is good to have.
Experienced with handling high-volume, high-dimensionality data for advanced analytics and data mining to deliver business intelligence and custom reporting solutions.
Comfortable working in fast-paced, deadline-driven environments, collaborating across business, analytics, and technical teams to translate solution requirements.
Skilled in leveraging multiple big data platforms and tools for delivering unified data views and actionable insights supporting product innovation and business growth.