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Job Description
Structured overview of role & requirementsAbout This Role
Develop and optimize data pipelines and ETL processes using SQL and AWS technologies like Redshift, Glue, EMR, and Kafka/Kinesis to ensure data accuracy and availability.
Resolve data engineering challenges by analyzing and integrating data from diverse sources, supporting complex queries aligned with business needs.
Automate data analysis and visualization workflows, document processes, and maintain compliance with regulatory standards.
Minimum Requirements
Bachelor's or Master's degree in Computer Science, Information Management, Data Science, Econometrics, AI, Applied Mathematics, Statistics, or equivalent.
Minimum 10 years of experience with a Bachelor's degree in relevant fields or no prior experience required with a Master's degree.
Strong knowledge of big data tools including AWS Redshift, Hadoop, and map reduce; familiarity with Airflow, AWS Glue, S3, AWS EMR, Kafka/Kinesis is desirable.
Work location: Hybrid with at least 3 days per week in-office attendance.
Ideal Candidate Profile
Experienced professional comfortable working under general supervision while independently solving data engineering problems and optimizing data pipelines.
Practitioner familiar with big data ecosystems, capable of integrating and automating data workflows to meet business and regulatory requirements.
Capable of documenting procedures clearly and providing actionable insights to business units, demonstrating cross-functional data expertise and operational impact.