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Tier-1 brand, popular mid-level Data Engineer title, metro location, and generalist skillset elevate competition.
Core data engineering skills (SQL, Python, AWS) are broadly transferable across industries despite fintech context.
Explicit 4–6 years requirement plus mandatory AWS, Redshift, SQL, and Airflow skills makes screening stringent.
Own the development and optimization of scalable, high-performance data pipelines and workflows using tools like Airflow, Redshift, dbt, and Kafka.
Lead the migration and evolution of on-premises data systems to AWS cloud infrastructure while ensuring data quality, reliability, observability, and security.
Collaborate cross-functionally with global product, engineering, analytics, and business teams to deliver robust data solutions supporting millions of users in a payments environment.
4-6 years of professional experience in Data Engineering or a related role.
Strong SQL expertise including query optimization and complex data modeling.
Proficiency in Python for data engineering and pipeline development.
Hands-on experience with AWS services (Redshift, Lambda, Glue, S3) and orchestration tools like Airflow.
Experienced in large-scale cloud migration projects and modern data transformation practices using dbt.
Familiar with real-time data streaming frameworks such as Kafka and CI/CD pipelines for data platforms.
Comfortable working in a fast-scaling fintech environment supporting high-volume global payments with a collaborative and proactive approach.