Data Engineer

A Data Engineer is sought to elevate our data platform to new heights. This role converges around designing, building, and troubleshooting data processing systems that are secure, reliable, fault-tolerant, scalable, and efficient. As a part of the elite Technology team, the candidate will be adept in tools and paradigms such as, data lakes, medallion architecture/Data Lakehouse, data warehousing, reactive systems, and Kappa/lambda architecture for data processing using open-source, PaaS and modern serverless technologies.

With a clear focus on geospatial data processing and a foundational grasp of Machine Learning, the role aims to fortify the seamless flow of high-quality data, ensuring robust insights for our business and clientele. This brings a lot of opportunities for you to shape the tools, technologies, and culture around data in the company.

• Responsible for the complete design, development, testing and optimization life-cycle of the Data Platform (data lakehouse, data pipelines, data warehousing, data marts, etc.).

• Engineer data solutions leveraging the medallion architecture and reactive systems principles to ensure optimal integration with data lakes and data warehousing.

• Ensuring that the data pipelines and general support infrastructure continue to run and operate in the most efficient manner, providing a mature ecosystem of data validation, data cleansing, monitoring and integrity testing.

• Designing, developing, and testing large stream data pipelines (stream or ELTs) to ingest, aggregate, clean, and distribute data products.

• Delve deep into geospatial data, crafting and optimizing processing techniques.

• Implementing features, technology, and processes that move us towards industry best practices, improving efficiency, scalability, security, and reliability.

• Provide operational support, bug fixes, and performance enhancements.

• Spearhead POCs to critically assess and onboard emerging tech paradigms.

• Interface with cross-functional teams, translating intricate data needs into efficient, scalable solutions.

• Responding to Incidents