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Popular mid-level data engineer title, 3-5yr band, and metro location create high candidate competition.
Core data engineering skills (Snowflake, AWS Glue, Python) are widely transferable across industries.
Explicit 3-5yr requirement plus mandatory Snowflake, AWS Glue, Python and SQL increases shortlist strictness.
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Design, develop, and maintain scalable data pipelines and data models in Snowflake for retail operations.
Build and optimize ETL workflows using Talend, AWS Glue, and SQL stored procedures integrating diverse data sources including MMS, CRM, Workday, and others.
Ensure efficient query performance and cost-effective data processing in Snowflake with proper documentation and compliance support.
3 to 5 years of data engineering experience, with at least 1 to 2 years working with Snowflake.
Strong hands-on experience with Snowflake, SQL stored procedures, and AWS Glue pipelines including Glue Jobs, Crawlers, and Data Catalog.
Proficient in Python for data engineering and automation; experienced with AWS services such as S3, Lambda, and Step Functions.
Bachelor's or master's degree in Computer Science, Data Science, Bioinformatics, or related field.
Experienced in cloud-based data environments, preferably AWS, with a focus on scalable data integration and transformation.
Familiar with retail data structures such as sales, customer, product, and workforce data domains.
Capable of collaborating with business stakeholders and regulatory teams to deliver compliant, optimized data solutions.