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Tier-1 brand, metro location, and broad full-stack data/ML requirements yield high competitor density.
Core big-data engineering skills transfer well, though payments domain experience gives moderate advantage.
Explicit 7+ years plus mandatory big-data and full-stack tech stacks make screening highly strict.
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Lead design and implementation of complex, full-stack analytics features focused on data-driven services and API delivery.
Develop and maintain scalable analytics and data models, ensuring high-quality, performant code and driving technical innovation within the team.
Mentor junior engineers and collaborate cross-functionally with product managers and designers to build data products that generate customer value.
7+ years of full stack engineering experience in an agile production environment.
Proficiency in Python or Scala, Spark, Hadoop platforms (Hive, Impala, Airflow, NiFi, Scoop), and SQL for building big data products.
Experience building and deploying production-level data-driven applications and pipelines, including machine learning systems at scale.
Bachelor's degree in Computer Science or related technical field.
Experienced leader in large-scale, complex full-stack engineering projects involving data analytics and big data technologies.
Able to bridge business and technical teams, quickly understanding use cases to deliver technical solutions that meet customer needs.
Strong track record of coaching teams, innovation in development processes, and delivering customer-centric analytical products.