Create and maintain optimal data pipeline architecture within AWS platform
Assemble large, complex data sets that meet business ? requirements. ?
Identify, design, and implement internal process improvements: automating manual ? processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc. ?
Ensuring the data quality throughout the data lake
5-10 years of experience as a data engineer.
Experience building data pipelines (ETL, data quality, data lineage)
Hands on experience working with Python (or other comparable language) and SQL
Experience with both traditional relational databases systems and big data tools such as: Hadoop, Spark, Presto, Kafka, etc. ?
Experience with AWS cloud services (or comparable cloud service): EC2, S3, EMR, RDS, Athena, Glue, etc.
Comfortable working in highly collaborative environment including: Scrum, Gitflow, PR reviews, pair programming, etc.
Pluses ?? : ?
Experience working with geospatial data
Experience performing root cause analysis on internal and external data and processes to ? answer specific business questions and identify opportunities for improvement. ?
Experience working with unstructured data. ?
Working knowledge of message queuing, stream processing, and highly scalable ? data stores. ?
Experience with data pipeline and workflow management tools: Airflow, Azkaban, ? Luigi, etc. ?
Experience with dataops using CI/CD is highly desirable
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Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody's Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.