Total experience 7+years.
Hands-on experience with Databricks on any cloud platform (Azure, AWS, or GCP).
Strong proficiency in Python, Scala, or SQL for data processing and scripting.
Solid understanding of Big Data concepts, distributed computing, and data lake house architecture.
Design, develop, and optimize scalable ETL/ELT pipelines using Databricks.
Experience with data pipeline orchestration tools (e.g., Airflow, Azure Data Factory).
Ensure data quality, performance tuning, and pipeline monitoring in production environments.
Provide technical leadership and contribute to architecture decisions for data platforms
Deep knowledge of and storage (Azure Data Lake, AWS S3, GCP Cloud Storage, etc.). cloud services.
Strong debugging, performance optimization, and problem-solving skills.
Should have good communication and customer handling skills.

RESPONSIBILITIES:

Writing and reviewing great quality code
Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements
Mapping decisions with requirements and be able to translate the same to developers
Identifying different solutions and being able to narrow down the best option that meets the clients’ requirements
Defining guidelines and benchmarks for NFR considerations during project implementation
Writing and reviewing design documents explaining overall architecture, framework, and high-level design of the application for the developers
Reviewing architecture and design on various aspects like extensibility,scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed
Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it
Understanding and relating technology integration scenarios and applying these learnings in projects
Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken
Carrying out POCs to make sure that suggested design/technologies meet the requirements.