5 - 10 years
14 - 20 Lacs
Posted:2 weeks ago|
Platform:
Hybrid
Full Time
Solid programming expertise, especially in Python, with strong fundamentals in computer science, data structures, algorithms, and system design.
Proven problem-solving ability with a focus on writing clean, maintainable, and efficient code.
Strong conceptual and practical understanding of end-to-end data platform architecturefrom ingestion to transformation to consumption.
Hands-on experience building and scaling data platforms in production environments.
In-depth knowledge and hands-on experience with AWS services relevant to data engineering, including:
Amazon EMR (both server-based and serverless) for large-scale data processing.
AWS Glue (including Glue Jobs, Glue Catalog, and Glue Data Quality features).
Amazon S3, Redshift, and Athena as key components of a modern data lake/data warehouse architecture.
Proficiency in building event-driven systems using:
AWS Lambda
API Gateway
Amazon SQS/SNS
EventBridge
Ability to integrate these services into scalable and decoupled data pipelines and microservices.
Familiarity with designing and working within microservices-based architectures, including service communication, deployment strategies, and monitoring.
This is a hands-on engineering role, requiring deep technical involvement in building, deploying, and maintaining the data platform.
Must be comfortable working independently as well as collaboratively in a fast-paced engineering environment.
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