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Tier-1 employer in Bangalore and mid-level Snowflake data engineer profile increases applicant competition moderately.
Snowflake/AWS specialization makes skills transferable across industries but still requires platform-specific experience.
Explicit 5–8 years and mandatory SnowPro plus specific Snowflake/AWS skills create strict shortlisting filters.
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Design, develop, and optimize data pipelines and data models primarily in Snowflake, ensuring data quality and governance.
Implement and maintain data transformation workflows using DBT and orchestrate workflows using tools like Apache Airflow.
Optimize Snowflake workloads for performance and cost, collaborate with stakeholders to understand data requirements, and automate deployment/testing with CI/CD tools.
5 – 8 years of relevant work experience in data engineering and analytics.
Mandatory skills: Snowflake, SnowPro Core Certification, SQL, Data Modelling, Python, AWS Glue, Lambda, Step Functions.
Preferred degree: MBA, Bachelor or Master of Engineering.
Experience with workflow orchestration (Apache Airflow) and CI/CD tools (Git, Jenkins, Azure DevOps) is expected.
Experienced in cloud-based scalable data solutions, especially on AWS with strong Snowflake expertise.
Skilled in building and optimizing complex data pipelines and workflows with a focus on performance and cost efficiency.
Comfortable working with multiple stakeholders including data analysts, scientists, and business teams to deliver actionable data insights.