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Strong fintech brand, popular Data Engineer mid-level role in metro yields high applicant competition.
Core data engineering skills transfer broadly, though payments/fintech domain experience is beneficial.
Explicit 2–3 year requirement plus mandatory SQL, Python, and AWS/Redshift/Airflow/dbt skills increases strictness.
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Build, optimize, and maintain scalable, high-performance data pipelines and workflows supporting real-time and batch data sources like MySQL and Kafka.
Design and maintain performant data models in AWS Redshift and contribute to cloud migration of data platforms to AWS.
Collaborate globally to translate business needs into robust technical data solutions embedding data quality, reliability, and security principles in a mission-critical payments environment.
2–3 years of professional experience in Data Engineering or related roles.
Strong SQL expertise including query optimization, complex transformations, and data modeling.
Proficiency in Python for data engineering and pipeline development.
Hands-on experience with AWS services (Redshift, Lambda, Glue, S3) and Airflow; familiarity with dbt for data transformation and modeling.
Experienced in building and scaling data pipelines in cloud environments, particularly AWS.
Comfortable working with real-time data streaming (Kafka) and modern orchestration tools (Airflow).
Able to contribute actively in cloud migration projects and maintain data platform performance in fintech or payments domain.