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Remote role, mid-level generalist data engineer title, and metro location increase applicant competition.
Core data engineering skills are broadly transferable across industries with minimal sector-specific constraints.
Explicit 5–7 years requirement plus mandatory AWS, Spark, Kafka, and ETL skills make filters stringent.
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Design, develop, and maintain large-scale, scalable data pipelines and infrastructure on AWS cloud platform.
Optimize data processing jobs for performance, scalability, and reliability using tools like Spark and Kafka.
Lead and mentor junior data engineers; collaborate with cross-functional teams to support advanced analytics and business objectives.
5 to 7 years of experience as a Data Engineer or similar role with emphasis on AWS cloud.
Proficient with AWS services such as S3, DMS, Lambda, EMR, Glue, Redshift, RDS (Postgres), Athena, Kinesis.
Strong programming skills in Python, PySpark, SQL/PLSQL, and experience with data modeling and ETL pipelines.
Bachelor’s degree in Computer Science, Engineering, or related field; Master’s preferred.
Experienced in deploying cloud-based data architectures like Data Lake, EDW, and data marts on AWS.
Demonstrated ability in implementing CI/CD pipelines for data engineering and familiarity with DevOps practices.
Skilled at managing end-to-end data solutions including monitoring, alerting, and cost optimization on cloud platforms.