Description:
- You should have experience in Implementation of various data processing patterns and data pipelines.
- Batch-based data pipelines
- Real Time streaming, event based
- Micro services based architecture
- Good appreciation and at least one implementation experience on processing substrates in BigData – Spark, Storm
- Exposure to varying databases – NoSQL (at very minimum Key value stores and/or Document stores), Appliances. Be able to cite implementation experiences, constraints and performance challenges in practice.
- You should have exposure to at least one Cloud, aware of the Server-less compute paradigm, PaaS, auto scaling, CICD, containerization
- Exposure to Streaming/Event based architecture – Unbounded, Bounded streams, Maintaining states (how to), constraints. Use of supporting technology blocks – low latency stores, messaging, decisioning.
- Well exposed to Consumption constructs for the data infrastructure- e.g. SQL on Hadoop, API/REST services, BI across the data landscape, Search and secondary indexing
- Overall appreciation of Security/RBAC and governance – at least one stack, third party tools
- Preferable (Nice to have) : Analytics pipelines, implementing analytic models on Big data infrastructure, Model orchestration in production workloads
Our strength is built on our ability to work together. Our diverse backgrounds offer different perspectives and new ways of thinking. It encourages lively discussions, inspires thought leadership, and helps us build better solutions for our clients. We want someone who thrives in this setting and is inspired to craft meaningful solutions through true collaboration.