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Popular data-engineer role, Bangalore metro, broad tech stack, and known fintech brand increase candidate competition.
Core data engineering skills (Python, Airflow, Snowflake, AWS) are broadly transferable across industries.
Explicit 2+ years plus mandatory Airflow, Snowflake, AWS, Python, and SQL requirements make filtering strict.
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Build and maintain scalable data pipelines using Airflow to ingest, transform, and deliver data into Snowflake and Databricks.
Design and implement data models in Snowflake to support analytics, reporting, and ML use cases focusing on performance and scalability.
Develop infrastructure as code with Terraform to automate cloud resource management and monitor pipeline health ensuring data quality and pipeline reliability.
Minimum 2+ years of data engineering experience with scalable data solution architecture.
Proficient in Python for data processing and automation.
Strong SQL skills and experience with Snowflake including performance optimization and data modeling.
Experience with AWS cloud services (S3, Lambda, EC2, IAM) and workflow orchestration tools like Airflow.
Has experience collaborating across functions including data analysts, data scientists, and business stakeholders to translate requirements into technical solutions.
Demonstrates ownership and proactive problem solving to ensure reliability and performance of data pipelines.
Comfortable working with ambiguous problems and driving independent progress with excellent communication on technical decisions.