Senior Data Engineer | GLS

Position Overview
Our client  is growing rapidly and seeking a strong Data Engineer to be a key member of the Enterprise Data and business Intelligence organization with a focus on data engineering services based in Bengaluru, India. You will be joining as one of the few first data engineers in our Bengaluru office and as the early engineers in the data platform. You will have an opportunity to help define our technical strategy and data engineering team culture in India. You will design and build data platforms and services while managing our data infrastructure in cloud environments that fuels strategicbusiness decisions across products.
A successful candidate will be a self-starter, who drives excellence, is ready to jump into a variety of big data technologies & frameworks, and can coordinate and collaborate with other engineers, as well as mentor other engineers in the team.
What You’ll Do

• Design and implement data management services for data trust, data compliance, data access, and metadata management in the form of scalable and configurable while clearly articulating the technical rationale behind your design and implementation choices
• Selecting and integrating any Big Data tools and frameworks required to provide requested capabilities
• Implementing ELT processes
• Monitoring performance and advising any necessary infrastructure changes
• Build data platforms and services to handle both real-time and batch processing of large data sets.
• Take end-to-end ownership of the design and implementation of core product functionality and key technical initiatives.

Requirements

You are perfect for the role if you have…

• 5+ years of data engineering experience in a fast-paced company that delivers software.
• A deep understanding of designing and building highly scalable Data warehouses and Data pipelines.
• Hands-on Experience in SQL, Java/Scala programming languages.
• Deep understanding of Apache Spark, Spark tuning, creating RDDs, and building data frames. Create Java/ Scala Spark jobs for data transformation and aggregation.
• Experience in building distributed environments using any of Kafka, Spark, Hive, Hadoop, etc.
• Good understanding of the architecture and functioning of Distributed database systems.
• Experience working with various file formats like Parquet, Avro, etc for large volumes of data.
• Experience with one or more NoSQL databases.
• Strong understanding of engineering best practices and design principles.