Location
Bangalore | India
Job description
- Engages technical teams and business stakeholders to discuss and propose data architecture approaches to meet current and future needs
- Defines the data architecture target state of their product and drives achievement of the strategy
- Ability to research and prototyping in iterative, feedback-led designs for data interfaces, APIs and pipelines for new and existing data products within JPMWM.
- Expertise in creating repeatable frameworks and processes for creating APIs and data pipelines that will enable standardized and transparent implementation patterns.
- Experience of identifying, prioritizing, aligning and negotiating features and functionality that deliver value or align with your wider business strategy.
- Evaluates recommendations and provides feedback for data, analytics and machine learning technologies
- Executes creative data architecture solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions and break down technical problems
- Develops secure, high-quality production code and reviews and debugs code written by others
- Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
- Bring in knowledge of best of the breed industry practices, tools and policies based on rich consulting expertise in domain of data engineering, data modernization and data repurposing to make enterprise data fit for purpose of both human and machine analytics and decision making.
Required qualifications, capabilities, and skills
- Hands-on practical experience delivering system design, application development, testing, and operational stability
- Advanced knowledge of architecture and one or more programming languages
- Proficiency in automation and continuous delivery methods and well known tools
- Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- In-depth knowledge of the financial services industry and their IT systems, their general interdependencies.
- Hands on experience on cloud IaC , PaaS and IaaS provisioning and configs, cost optimized capacity design, volumetrics and planning.
- Practical cloud native experience, especially on big-data, high volume data parallel processing and data lakes APIs
- Ability to evaluate current and emerging technologies to recommend the best data architecture solutions for the future state architecture
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