Başlyk:

Çikgi

- Data Access, Transform, Processing, and Reporting Needs. - Data Lake Ecosystem bilen baglanyşykly iş bölümleri we data science toparlary bilen data elýeterliligi, transformasiýa, işleme we hasabat talaplary barada hyzmatdaşlyk et. - Data Lake ekosistemasy bilen baglanyşykly iş ýerine ýetirme, tehnika meseleleri we okuwlary golda. - AWS resurslaryny, EMR we ECS klasterleri bilen dolandyrmak üçin topar bilen işle. - AWS aletleriniň üpjünçiligini, gözegçiligini, konfigurasiýasyny we saklamagy golda. - Aýalmak we täze bulut tehnologiýalaryny hödürlemek we hödürlemek, olar mümkinçiligini we işleýiş çykdajylaryny peseltýär. - Infrastructure as Code with Terraform we CI/CD tools such as Jenkins bilen automatizasiýa tagallalaryny golda. - Data Governance, Access Control, and Security Risk Reduction implementing team with work. Required experience - 7-9 years of experience designing and developing cloud-based data models, ETL pipelines, and infrastructure. - Structured and unstructured data working experience. - SQL with strong proficiency across popular databases. - SQL engines configuration experience. - Resource requirements planning from high-level specifications. - Common database issues troubleshooting experience. - Spark, Glue, EMR, and Apache Kafka or AWS Kinesis with experience. - Version control tools such as Git or Subversion with experience. - Automatic build systems and CI/CD workflows using experience. - Java, Python, and Scala programming experience. - Data Structures and algorithms knowledge.

- Relasional, NoSQL, graph, document, key-value, and time-series databases knowledge. - Scalable data model design and management knowledge. - ML model deployment knowledge. - AWS cloud platforms knowledge. - TDD and BDD knowledge. - Software development skills, frameworks, and technologies improvement in strong interest. Engagement highlights - Data modeling, data services, and data science across a broader Data Intelligence Platform working opportunity. - AWS, ETL pipelines, databases, search technologies, and recommendation systems covering a diverse technical environment exposure. - Data science teams and internal stakeholders on reporting, transformation, and platform capabilities directly collaboration..

Saýlaw üçin: https://weworkremotely.com/remote-jobs/toptal-senior-data-engineer-aws-data-lake-pipeline-architecture