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Mid-level generalist data engineering role with popular title, metro hiring, and recognizable brand increases competition.
Core cloud data engineering skills (AWS Glue, Redshift, Python) are broadly transferable across industries.
Explicit 4–6 years plus mandatory AWS Glue, cloud DW, Python, and SQL skills enforce strict filtering.
Design, develop, and maintain scalable data pipelines and ETL/ELT workflows primarily using AWS Glue and Python.
Build and optimize cloud data warehouse solutions using Amazon Redshift and Snowflake, and manage relational and NoSQL databases (Amazon RDS, DynamoDB).
Ensure data quality, security, governance, and operational resilience while collaborating with cross-functional teams to deliver business-focused data solutions.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field.
4–6 years of experience in Data Engineering or Cloud Data Platform development.
Hands-on expertise with AWS data services including AWS Glue, Lambda, Amazon Redshift/Snowflake, Amazon RDS, and DynamoDB.
Proficiency in Python programming and strong SQL skills for data processing and pipeline development.
Experienced in designing and supporting large-scale, cloud-based data architectures focused on scalability and cost-efficiency.
Familiar with Agile and DevOps practices and capable of collaborating effectively with technical and business stakeholders.
Likely to hold or pursue AWS certifications and have exposure to Infrastructure as Code tools and CI/CD automation.