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Tier-1 brand, mid-level data engineer title, metro location, broad cloud/Snowflake skillset amplify competition.
Core data engineering skills are transferable across industries but Snowflake/consulting context adds some specificity.
Mandatory SnowPro certification, explicit 5–8 years, and specific Snowflake/AWS/DBT stack increase screening strictness.
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Design, develop, and optimize data pipelines and data models primarily in Snowflake, ensuring data quality and governance.
Implement and maintain DBT workflows and automate deployment/testing of data workflows using CI/CD tools.
Collaborate with cross-functional teams and leverage AWS cloud services to build scalable data solutions and optimize Snowflake workloads.
5-8 years of work experience in data engineering with Snowflake expertise.
Mandatory Snowflake SnowPro Core certification.
Proficient in Snowflake, SQL, Data Modelling, Python, and AWS services (Glue, Lambda, Step Functions).
Educational qualification: BE, B.Tech, ME, M.Tech, MBA, or MCA with 60%+ marks.
Experienced in modern cloud data engineering with hands-on expertise in Snowflake and AWS cloud platforms.
Skilled in workflow orchestration tools like Apache Airflow and automation using CI/CD practices.
Analytical mindset with strong problem-solving abilities and familiarity with data transformation tools like DBT.