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Tier-1 employer, mid-level generalist data engineer, and metro/hybrid posting increase competition.
Data engineering skills transfer across industries but require specific cloud data platform experience.
Explicit 5–8 years plus mandatory Snowflake, ETL, Kafka, Python and database requirements create strict filters.
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Develop and maintain scalable data processing platforms and pipelines supporting Corporate Functional Data IT.
Ensure data availability through data integration and implementation solutions, including data quality and compliance management.
Collaborate with engineering and platform teams to deliver data solutions on-premises and cloud, contribute to automation framework development, and participate in full software development lifecycle.
5-8 years of experience in Data Warehousing (DWH) with strong understanding of ETL processes and tools.
Bachelor’s degree in engineering, Technology, or a related field.
Expertise in cloud data platforms and database technologies such as Snowflake.
Strong experience with ETL tools like Informatica and DBT, data streaming technologies such as Kafka, and scripting/programming skills in Unix shell scripting, Python, and SQL.
Experienced in building and optimizing big data pipelines with focus on data quality and compliance frameworks.
Operates well in cross-functional and collaborative engineering teams delivering end-to-end data solutions in cloud or hybrid environments.
Capable of innovating on data infrastructure with some exposure to automation and real-time data processing systems.