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Tier-1 brand, mid-level experience, and metro location increase competition, but niche data pipeline skills moderate density.
Core data engineering skills transfer across industries, though banking domain and risk context add moderate sensitivity.
Explicit 5+ years requirement plus platform and data pipeline skills create moderate filtering of candidates.
Lead complex, company-wide technology initiatives ensuring scalable, robust software solutions.
Set and enforce engineering standards and best practices across teams for large-scale technology projects.
Collaborate with technical experts and lead teams by mentoring, conducting design reviews, and resolving complex technical challenges.
5+ years of software engineering experience (including equivalent training, military, or education).
Experience with distributed systems design focusing on scalability, fault tolerance, and data consistency trade-offs.
Experience building distributed data pipelines using Apache Beam, Flink, or Spark.
Not explicitly mentioned: mandatory degree, location, or notice period requirements.
Technically proficient leader with strong expertise in distributed data architectures, microservices (Spring Boot), and containerization (Kubernetes).
Experience designing end-to-end analytics architectures from ingestion to visualization with focus on reliability and operability (monitoring, alerting, incident management).
Comfortable defining engineering standards and influencing cross-team technical direction in large complex environments.