Leads end-to-end delivery of full-stack, big data, and generative AI engineering initiatives. Coordinates technical teams, dependencies, milestones, risk mitigation, governance, and stakeholder communication. Oversees modern application architectures using Java, Python, databases, messaging systems, Kubernetes, cloud platforms, and AI frameworks. Drives Agile, CI/CD, DevOps, SDLC compliance, and continuous improvement while resolving complex technical issues across distributed systems.
The Senior Big Data Solutions Lead, Vice President is a senior level position responsible for establishing and implementing new or revised application systems and programs in coordination with the Technology team. The overall objective of this role is to lead applications systems analysis and programming activities.
Responsibilities:
- Project Planning & Execution: Coordinates end-to-end delivery of full-stack and GenAI engineering projects, identifying technical resource requirements, managing cross-functional dependencies, and establishing sprint and milestone schedules.
- Technical Delivery : Oversees technical deliverables across modern tech stacks—including backend services (Python, Java, REST APIs), frontend frameworks, relational databases (PostgreSQL, MySQL), NoSQL stores (MongoDB, DynamoDB, Couchbase), and containerized platforms (OpenShift, Kubernetes, AWS ECS) including KDB.
- AI & Innovation Integration: Tracks and coordinates proof-of-concepts (POC's) and production implementations involving Generative AI frameworks (e.g., Lang Chain, Open AI API, Hugging Face models), ensuring alignment with enterprise architecture and AI safety policies.
- Risk, Governance & Control: Verifies adherence to strict software development lifecycle (SDLC) controls, architectural standards, change management protocols, information security policies, and regulatory compliance.
- Issue & Dependency Management: Determines scope, root causes, and impacts of technical risks, blockers, and defect backlogs; actively drives cross-team resolution and mitigation strategies.
- Stakeholder Collaboration: Bridges communication between software engineers, architects, data teams, product owners, and business leadership to align technical solutions with business goals.
- Evaluative Decision-Making: Provides evaluative judgment based on deep analysis of factual project and architecture data in complex, distributed systems environments.
- Continuous Improvement: Drives adoption of Agile/Scrum best practices, CI/CD pipeline automation, and modern DevOps/cloud standards to optimize engineering throughput.
- Operational Excellence: Appropriately assesses risk when business and technical decisions are made, demonstrating particular consideration for the firm's reputation and safeguarding assets by driving compliance with applicable laws, rules, and regulations, adhering to Policy, and escalating control issues with transparency.
Qualifications:
- 10–12 years of relevant experience in IT/Technology as a delivery lead.
- Technical Acumen: Practical understanding of fullstack development lifecycles, backend frameworks (Java, Python), and modern API design (RESTful APIs, microservices architecture).
- Data Architecture Knowledge: Familiarity with relational database concepts (PostgreSQL, MySQL) and NoSQL document/key-value stores (MongoDB, DynamoDB, Couchbase) & KDB for dealing with timeseries data.
- Cloud & Containerization: Working knowledge of container management and orchestration platforms (Kubernetes, Red Hat OpenShift, AWS ECS) and CI/CD pipelines.
- Generative AI & LLMs: Exposure to or experience coordinating initiatives leveraging Generative AI, LangChain, OpenAI API, and Hugging Face toolkits/libraries.
- Analytical & Problem-Solving: Superior ability to dissect complex system architectures, anticipate delivery bottlenecks, and resolve cross-team technical dependencies.
- Communication & Influence: Excellent diplomacy, verbal/written communication, and stakeholder management skills with both technical and executive audiences.
Education & Requirements:
- Bachelor’s degree/University degree or equivalent experience
- Master’s degree preferred
- Must have hands-on experience in Java and Python
- At least 10 -12 years overall software development experience on majorly working with handling application with large scale data volumes from ingestion, persistence and retrieval.
- 5+ years of experience in leading a small to medium-size development teams
- Proficiency in enterprise level application development using Java 17,scala, Oracle (or comparable database) and Messaging infrastructure like Solace, Kafka, Tibco EMS
- Experience with developing Microservices using Kubernetes or ECS
- Good knowledge of Distributed databases/ Caching technologies like Gemfire, Apache Ignite, Couchbase
- Proficient with concepts like Time Complexity, Distributed Computing
- Proficient with test-driven (TDD) and behavior-driven development (BDD) concepts and tools
- Proficient with Data structures, Algorithms and Design patterns.
- Proficient with shell scripting in Linux
- Knowledge of core banking/financial services systems for Capital Markets asset classes like FX, Equities, Rates is a plus
- Strong knowledge in Big data echo system is a plus
This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned as required.
#LI-Hybrid
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Job Family Group: Technology------------------------------------------------------
Job Family:Applications Development------------------------------------------------------
Time Type:Full time------------------------------------------------------
Most Relevant Skills Please see the requirements listed above.------------------------------------------------------
Other Relevant Skills For complementary skills, please see above and/or contact the recruiter.------------------------------------------------------
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