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Remote role, common Data Engineer title, mid-level (5+ years) and broad AWS skillset increase applicant competition.
AWS data engineering skills transfer across industries but require cloud-specific experience, so moderate transferability.
Explicit 5+ years requirement plus many mandatory AWS technologies and programming skills raises filter strictness.
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Design, build, and maintain scalable data pipelines and applications on AWS including data lakes and warehouses.
Lead and oversee a team of data engineers ensuring alignment to business objectives and continuous improvement of data processes.
Architect and implement end-to-end AWS data solutions including serverless applications, streaming solutions, and CI/CD strategies.
Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent.
5+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.
Strong proficiency in Python, Shell scripting, SQL, and core AWS services including Glue, Redshift, S3, Lambda, EMR/Spark, and associated security tools.
Experience with serverless application development, data pipeline orchestration, and system design for AWS ingestion pipelines.
Experienced in complex, large-scale AWS data engineering environments with deep hands-on coding and architecture capabilities.
Capable of independently leading architecture discussions, performing development tasks, and driving adoption of new AWS technologies and best practices.
Skilled in implementing cost-effective, reliable, and scalable data ingestion and processing solutions including streaming and CI/CD pipelines.