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Tier-1 brand, mid-level generalist role, 3-6 years, and broad AWS skillset make competition high.
Core data engineering skills are transferable, but finance domain experience increases sensitivity to background.
Explicit 4+ years and mandatory data engineering experience create moderately strict shortlisting.
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Lead design and implementation of complex, scalable data architectures and large-scale AWS data pipelines for finance technology.
Develop and maintain end-to-end data engineering solutions including ETL, data warehousing (Redshift), and analytics applications for business insights and automation.
Provide technical leadership, establish best practices, and collaborate cross-functionally to deliver auditable and maintainable data solutions.
Minimum 4 years of experience in data engineering with data modeling, warehousing, and ETL pipeline development.
Proficiency in SQL and experience working cross-functionally with technical teams.
End-to-end ownership of major project deliverables and business intelligence solutions (data warehousing and BI tools).
Experience with AWS data technologies (Redshift, S3, Glue, EMR, Kinesis, Lambda, IAM) preferred but not mandatory.
Experienced with large-scale AWS data environments and AWS finance data or fintech domains.
Able to lead complex technical projects, design scalable architectures, and resolve system-wide data challenges.
Skilled in implementing data governance, security standards, and mentoring teams across multiple projects.