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Mid‑senior generalist Data Engineer role with broad Hadoop/Spark/cloud requirements at a known fintech, driving high applicant density.
Core data engineering skills (Hadoop, Spark, SQL) transfer easily across industries despite preferred credit-card domain knowledge.
Mandatory 8–10 years plus Hadoop/Spark/SQL and data warehousing expertise makes screening highly selective.
Develop and maintain data ingestion pipelines and infrastructure for internal and external data sources, ensuring data quality and process monitoring.
Collaborate with data architects, engineers, and business users to manage data models, build analytical tools, dashboards, and support marketing analytics data ecosystem.
Provide subject matter expertise on data domains and business processes, automate data-centric workflows, and support new analytical proofs of concept and tool explorations.
Bachelor’s degree in Computer Science, Information Systems, or equivalent; Master’s degree in Computer Science or STEM preferred.
8-10 years of IT experience including SQL, Hadoop Ecosystem, data warehouse, data modelling.
Experience with Agile project management frameworks (e.g., JIRA) and developing software using agile methodologies.
Expertise in metadata management tools and ER studio.
Experienced data engineer with strong background in credit card, banking, financial, or retail data domains and credit card regulations.
Operates effectively in Agile environments, collaborates with cross-functional teams including marketing analytics, architects, and business users.
Experienced in big data technologies (Hadoop, Spark), cloud environments (AWS, Azure), and automation of data pipelines and tools.