
Senior Manager, Data Engineer
- Bangalore, Karnataka
- Permanent
- Full-time
- Act as a trusted advisor to VISA's clients, understanding their business objectives and data challenges. Provide strategic guidance on designing and implementing scalable data architectures to support advanced analytics and marketing use cases.
- Collaborate with senior management, business units, and IT teams to gather requirements, align data strategies, and ensure successful adoption of solutions.
- Collaborate with multiple business units to understand data requirements and to integrate diverse data sources in batch and real time to create a consolidated view such as single customer view.
- Support Design, development, and deployment of robust data platforms and pipelines (on cloud and on-premises), leveraging technologies such as Hadoop, Spark, modern ETL frameworks and APIs.
- Ensure data solutions adhere to client-specific governance and regulatory requirements related to data privacy, security, and quality.
- Design target platform components, data flow architecture and capacity requirements for scalable data architecture implementation.
- Hands-on design, development, deployment and support of strategic or bespoke client projects using big data technologies within VISA.
- Develop and deliver training materials, documentation, and workshops to upskill client teams and promote data best practices.
- Review scripts for best practices, educating user base and building training assets for beginner and intermediate users.
- Certification in Big Data architecture and platform such as Hadoop and Apache Spark preferred.
- Proven experience designing and developing large scale, production grade systems utilizing best-in-class software engineering practices, including DevOps, CICD pipelines, and automation technologies.
- Advanced experience in Python, PySpark scripting, SQL queries, ETL and data streaming technologies, cloud and non-cloud based big data technologies such as Databricks, Snowflake, Sagemaker, etc.
- Experience in deployment, operationalization of Machine Learning models using MLOps techniques
- Experience with API integration and deploying containerized applications (e.g, Docker, Kubernetes).
- Good understanding of data governance topics such as metadata management, data quality management, master data management and data security management.
- Good understanding of Agile way of working, tools such as JIRA and practical experience of working in Agile teams.
- Expertise in dashboard and report development using visualization tools such as Tableau, MicroStrategy will be an advantage
- Experience with marketing cloud solutions such as Salesforce will be an advantage.
- Very strong people, technology and project management skills and experience
- 12 plus years of progressive experience in data advisory, data architecture & governance and data engineering roles
- Good understanding of Banking and Financial Services domains, including familiarity with enterprise analytics data assets.
- Experience in client consulting on data architecture and engineering solutions, with demonstrated ability to translate business needs into technical requirements
- Demonstrated expertise in distributed data architecture, modern business intelligence (BI) tools, and frameworks/packages used for Generative AI and machine learning model development
- Strong appreciation for data science concepts, including hands-on experience with machine learning algorithms, feature engineering, and model evaluation techniques.
- Excellent presentation, communication, and interpersonal skills, with the ability to effectively engage stakeholders at various organizational levels.
- Demonstrated aptitude for rapid learning and adoption of emerging technologies, methodologies, and paradigms in the evolving data science landscape.
- Proven ability to integrate new techniques and technologies to address complex business challenges and drive innovation.
- Strong resource planning, project management, and delivery skills, with a track record of successfully leading or contributing to large-scale data initiatives.
- Ability to influence senior management within and outside Analytics groups
- Ability to collaborate and successfully persuade/influence internal stakeholders for building best-in-class solutions