Position: Databricks Engineer
Location: Bangalore

Job Description
The successful candidate will be:

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 efficient 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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