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Strong employer brand, metro location, mid-level data engineer title increase applicant competition.
Data engineering skills are transferable but Snowflake/Azure specialization moderately limits cross-industry fit.
Explicit 5-8 years plus mandatory Snowflake, Azure, and Python makes filtering stringent.
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Design, build, and optimize cloud-based data warehousing and analytics solutions using Snowflake, focusing on data ingestion, ELT pipelines, and query performance tuning.
Implement data security and governance controls including Role-Based Access Control, data masking, row-level security, and secure data sharing within Snowflake.
Integrate Snowflake with cloud environments (Azure mandatory) and third-party ETL/ELT tools like dbt, Airflow, or Matillion, leveraging programming in Python and SQL.
5 to 8 years of experience in data engineering or Snowflake-specific roles.
Strong hands-on experience with Snowflake platform (mandatory).
Mandatory cloud experience with Microsoft Azure.
Proficiency in Python and SQL programming languages; educational qualification: B.E, B.Tech, MCA, M.E, or M.Tech.
Experienced data engineer with expertise in building scalable Snowflake data pipelines and optimizing warehouse performance in cloud environments.
Operates effectively in roles requiring data security governance, advanced data modeling, and integration with third-party ETL tools.
Comfortable working in strategic advisory settings focusing on data analytics and able to leverage advanced analytical and scripting skills for business problem-solving.