Software Engineer III - Big Data Databricks, Python / Java

Overview In this role you’ll help design and build a secure, scalable data platform for KYC and risk assessment within an agile data engineering team. You will deliver production-grade code, create reusable frameworks, and leverage AI-assisted development to raise quality and speed. You’ll collaborate with cross-functional partners, applying cloud, data, and ML capabilities to enterprise-scale data processing. This is a chance to impact risk and compliance capabilities for a global financial institution with a strong engineering culture. Compensation / Benefitsbase salary determined by role, experience, and locationcommission-based pay and/or discretionary incentive compensation (eligible roles)comprehensive health care coverageretirement savings plantuition reimbursementmental health support ResponsibilitiesDevelop secure, high-quality production code for data-intensive applications and platformsCreate durable, reusable software frameworks and patterns used across teamsLeverage enterprise-approved AI coding assist tools to improve code quality, delivery speed, and productivity with peer review and secure coding standardsApply SDLC tools and AI-assisted development to enhance automation value at scaleAdvise cross-functional teams on technological matters within domain of expertiseDemonstrate secure handling of inputs/outputs and responsible AI practices Key requirementsFormal training or certification on software engineering concepts5+ years of applied software engineering experienceHands-on experience delivering system design, development, testing, and operational stability at enterprise scaleExpert in Python and/or JavaDeep knowledge of software development with emphasis on cloud, AI/ML, or data engineeringExperience using enterprise-authorized AI-assisted development tools with ability to validate AI outputs for correctness, performance, and securityKnowledge of responsible AI use in engineering workflows, data sensitivity, and security expectationsExperience with large-scale data processing, microservices, API design, Kafka, Redis, Memcached, observability tools (Dynatrace, Splunk, Grafana), and orchestration frameworks (Airflow, Temporal)Working knowledge of relational and NoSQL databases, data lakes, data governancePractical cloud-native experience (AWS, Azure, or GCP)Ability to present to senior leaders and executivesCommunication with senior leaderscollaboration across teamsproblem solving and critical thinkingPythonJavacloud platforms (AWS/Azure/GCP)