Data Engineering Job Openings At JLL Technologies | Bengaluru

Qualifications

• 0+ years’ overall work experience and Bachelor’s degree in Information Science, Computer Science, Mathematics, Statistics or a quantitative discipline in science, business, or social science.
• Knowledge of using Python, Kafka, Spark Streaming, Azure SQL Server, Cosmos DB/Mongo DB, Azure Event Hubs, Azure Data Lake Storage, Azure Search etc.
• Hands-on Experience for building Data Pipelines in Cloud would be a plus.
• Design & develop data management and data persistence solutions for application use cases leveraging relational, non-relational databases and enhancing our data processing capabilities.
• Experience handling un-structured data, working in a data lake environment, leveraging data streaming and developing data pipelines driven by events/queues will be an advantage
• Team player, Reliable, self-motivated, and self-disciplined individual capable of executing on project within a fast-paced environment working with cross functional teams

Job Description & Responsibilities:

Data Engineer is self-starter to work in a diverse and fast-paced environment that can join our Enterprise Data team. This is an individual contributor role that is responsible for developing of data solutions that are strategic for the business and built on the latest technologies and patterns. This a global role that requires partnering with the broader JLLT team at the country, regional and global level by utilizing in-depth knowledge of data, infrastructure, technologies and data engineering experience.

As a Data Engineer 1 at JLL Technologies, you will:

• Contributes to the development of information infrastructure, and data management processes to move the organization to a more sophisticated, agile and robust target state data architecture
• Develop systems that ingest, cleanse and normalize diverse datasets, develop data pipelines from various internal and external sources and build structure for previously unstructured data
• Develop and operate modern data architecture approaches to meet key business objectives and provide end-to-end data solutions
• Develop good understanding of how data will flow & stored through an organization across multiple applications such as CRM, Broker & Sales tools, Finance, HR etc
• Develop data management and data persistence solutions for application use cases leveraging relational, non-relational databases and enhancing our data processing capabilities