Responsibilities:
- 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.