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Pan-India hybrid mid-level (3–5 yrs) role with common automation skills increases candidate competition.
Requires specific data-platform testing, cloud, and streaming skills, moderately limiting industry transferability.
Explicit 3–5 years plus mandatory Python, DBT, Airflow, Snowflake, Kafka, AWS, CI/CD and IaC skills increases selectivity.
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Build and maintain scalable frameworks for data platforms to enhance system reliability and reduce production incidents.
Develop and manage test frameworks, libraries, CLI tools in Python, and ETL/ELT workflows using tools like DBT, Airflow, and Snowflake.
Implement and manage integration and delivery pipelines including Kafka/Kinesis systems, CI/CD with Jenkins/GitHub Actions, AWS data and compute services, and infrastructure via Terraform or CloudFormation.
3–5 years of relevant work experience in automation or quality engineering focusing on data platforms.
Strong proficiency in Python for developing test frameworks, libraries, and CLI tools.
Advanced SQL skills for data validation and reconciliation.
Hands-on experience with ETL/ELT workflows using DBT, Airflow, and Snowflake; integrating Kafka/Kinesis; managing CI/CD pipelines and AWS services; plus Infrastructure as Code tools like Terraform or CloudFormation.
Experienced in end-to-end automation with a focus on large-scale data platform reliability and quality assurance.
Comfortable with cross-functional collaboration to resolve event processing and delivery semantic challenges.
Capable of operating independently in a hybrid environment with strong technical ownership of data engineering and automation processes.