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Tier-1 brand, metro location, and mid-level data engineer role increases applicant competition.
Snowflake and Azure specialization increases domain bias but core data engineering skills remain transferable across industries.
Explicit 5-8 years plus mandatory Snowflake, Azure, Python and SQL requirements create strict shortlisting filters.
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Design and implement scalable data models and schemas within the Snowflake platform to support analytics solutions.
Develop and maintain ELT pipelines using Snowflake features (SQL, Snowpipe, Streams, Tasks, Snowpark) and Python for data ingestion and transformation.
Optimize data warehouse performance and implement data security protocols including RBAC, data masking, and secure data sharing on cloud environments (primarily Azure).
5 to 8 years of experience in data engineering or Snowflake-specific roles.
Strong hands-on expertise in Snowflake platform, Azure cloud, Python programming, and advanced SQL required.
Educational qualification: Bachelor of Engineering, Bachelor of Technology, MCA, M.E, or M.Tech.
Not explicitly mentioned in the JD: notice period requirement and work visa sponsorship details.
Experienced in integrating Snowflake with third-party ETL/ELT tools such as dbt, Airflow, or Matillion in cloud environments.
Capable of monitoring and tuning data warehouses for cost-efficiency and performance at enterprise scale.
Strong background in database principles, advanced SQL, and programming for complex data pipeline and transformation development.