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Tier-1 brand, generalist senior software title, mid-level experience, and metro location increase candidate competition.
Core Databricks/Spark/cloud skills are transferable, but compliance surveillance domain knowledge increases specificity.
Explicit 5+ years plus many mandatory techs (Databricks, Spark, Java/Python, AWS, Kafka) raises filtering strictness.
Design, develop, and optimize scalable, fault-tolerant microservices, APIs, and data pipelines using Databricks, Apache Spark, and Delta Lake.
Drive adoption of AI-assisted engineering best practices and automation within the SDLC to improve code quality, delivery, and operational outcomes.
Partner with product and compliance teams to enhance alert accuracy and proactively identify communication data issues to improve detection quality.
5+ years of applied software engineering experience with formal training or certification.
Expertise in Java/Kotlin, Python, Databricks (Spark, Delta Lake, Workflows), and cloud-native microservices architecture.
Proficient with AWS services (EC2, ECS, EKS, EMR, S3, Glacier), Kafka, PostgreSQL, and CI/CD tooling (ArgoCD, Helm, Terraform, Jenkins, GitHub Actions).
Experience with Test-Driven Development and delivering services with SLI/SLO/SLAs.
Senior-level technical leadership experience involving mentoring engineers and driving adoption of best practices in complex, compliance-focused financial environments.
Strong expertise in cloud-native, large-scale batch and streaming data pipelines incorporating ML/LLM models in production.
Experience operating in agile teams delivering secure, scalable data engineering solutions with emphasis on observability and operational stability.