Design, build, and optimize end-to-end data pipelines for large structured and unstructured data. Implement near-real-time ETL, data validation, monitoring, and performance optimization. Collaborate with stakeholders, document designs and workflows, and provide technical guidance to the team.
Location: Pune
Responsibilities include:- Design, implement, and optimize end-to-end data pipelines for ingesting, processing, and transforming large volumes of structured and unstructured data.
- Develop data pipelines to extract and transform data in near real-time using cloud-native technologies.
- Implement data validation and quality checks to ensure accuracy and consistency.
- Monitor system performance, troubleshoot issues, and implement optimizations to enhance reliability and efficiency.
- Collaborate with business users, analysts, and other stakeholders to understand data requirements and deliver tailored solutions.
- Document technical designs, workflows, and best practices to facilitate knowledge sharing and maintain system documentation.
- Provide technical guidance and support to team members and stakeholders as needed.
- 8+ years of work experience.
- Proficiency in writing complex SQL queries on MPP systems (Snowflake/Redshift).
- Experience in Databricks and Delta tables.
- Data engineering experience with Spark/Scala/Python.
- Experience in Microsoft Azure stack (Azure Storage Accounts, Data Factory, and Databricks).
- Experience in Azure DevOps and CI/CD pipelines.
- Working knowledge of Python.
- Comfortable participating in 2-week sprint development cycles.
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