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Mid-level, metro location, broad AWS skillset, and recognizable Rocket brand increase candidate competition.
Role requires specific cloud data platform and AWS experience, making transfers moderately sensitive across industries.
Explicit 4–6 years plus mandatory AWS Glue, Redshift/Snowflake, Python, and related cloud skills raise filtering strictness.
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Design, develop, and maintain scalable data ingestion, transformation, and processing pipelines using AWS services including Glue, Lambda, Redshift, Snowflake, RDS, and DynamoDB.
Ensure data quality, integrity, security, and governance across cloud data platforms while optimizing for scalability, performance, operational resilience, and cost efficiency.
Collaborate with global engineering, analytics, product, and business teams to deliver reliable and business-focused data solutions, participate in architecture and code reviews, and support production pipeline monitoring and troubleshooting.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or related technical field.
4–6 years of experience in Data Engineering, Data Integration, or Cloud Data Platform development.
Hands-on experience with AWS data and analytics services, including AWS Glue for ETL, Amazon Redshift and/or Snowflake, Amazon RDS, Amazon DynamoDB, and AWS Lambda.
Proficiency in Python for data processing and automation, strong SQL skills, and experience designing and supporting large-scale cloud data pipelines.
Experienced in building and optimizing large-scale, cloud-native data architectures primarily on AWS with strong focus on ETL/ELT workflows and serverless data applications.
Familiar with agile development and DevOps practices, with experience in continuous improvement initiatives and collaborative cross-functional partnerships.
Holds or is pursuing AWS Certifications and has knowledge of Infrastructure as Code tools, data governance, and modern data lake architectures.