- Big Data engineer having extensive coding experience in Spark & Scala. He/She should be able to work well within a product-based organization (product mindset) and with a team comprising of developers & functional experts on a critical customer-facing product. Has prior experience of at least 2 years as a PO, or lead business analyst and is comfortable with technical products.
- Should have handled one e2e implementation of creating a data pipeline using spark and in-depth knowledge of spark performance tuning.
- Good to have experience in microservices-based architecture.
- Autonomous, motivated and self-driven.
- The candidate should have some prior experience in managing direct customer communication and expectations management and ability to handle ambiguity.
- The candidate should have strong stakeholder management skills to manage dependencies across multiple teams and lead discussion with multiple stakeholders.
- Support continuous improvement by investigating alternatives and technologies and presenting these for architectural review.
- Ready to work with a DevOps mindset with other engineers.
- Candidate should be able to understand Application architecture and align with overall product functionality and vision.
- Excellent English verbal and written communication skills.
- Strong analytical and Conceptual Thinking to perform effective root cause analysis and drive resolutions.
- Airline industry knowledge is a strong positive.
Technical Skill
- 10+ years of experience in analysis, design, development, documentation, implementation, and testing of software products using Spark, Scala and Big data tech stacks
- At least 6+ years of working with Big Data Tech stacks: Databricks, Kafka, Spark, and experience on Azure cloud platform.
- Good to have experience with NoSQL Data using MongoDB/Cassandra/HBase etc.
- Good to have experience in microservices-based architecture.
- Sound Knowledge of OOPs concepts (Class loading, Memory Management, Transaction management, Multithreading, Garbage collection, Performance optimization), Data structures, and Design Patterns.
- Sound experience with Streaming data using Apache Kafka and processing it in real time with optimum performance.
Experience in Messaging architecture using MQ is a plus.
- Designing and developing high-volume, low-latency applications for mission-critical systems and delivering high availability and performance.
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