Bakı,
Azərbaycan
27.02.25
-
27.03.25
İş haqqında məlumat
- Execute Data Strategy within Data Architecture and Data Platforms Environment;
- Research, design and propose new features or optimizations initiatives for various functional areas having agility and digitalization in mind;
- Participate in Specific Streams under Data Architecture topic to create synergy between Backend Transactional Systems, Backend Analytical and Reporting Systems and Core Systems;
- Work in particular stream/squad with business representatives and teams to collect and translate information requirements into data to develop data-centric solutions;
- Apply principles and standards for modeling, stored procedures, replication, regulations, and security, among others, to meet technical and business goals defined by company;
- Participate in Development phases of data-related services using various technologies and architectural patterns for enabling and supporting purposes of existing reporting and analytical use cases for internal and external use cases;
- Work in the squads on products as well as internal stakeholders to create new products, features in products as well as identify the root causes of problems, turn analyses into insights and solutions;
- Participate in project implementation and operational tasks execution;
- Participate in quality management of Data Stack by having Test Driven Development approach, having UNIT, Integration and Regression tests within Development Lifecycle;
- Deliver the documentation according the company defined documentation standards for Data Stack and constantly deliver documentation within delivery Agile Sprints or within Waterfall Milestones.
Tələblər
- Higher Education;
- 1+ years of work experience in Data Engineering or Software Engineering positions within Telco, Banking and Retail industry;
- Good hands-on experience in data ecosystems; covering data ingestion, data modeling, and data provisioning to consumers and downstream systems;
- Good coding skills in at least two relevant languages (e.g. SQL, Python, Java, Scala) as well as excellent knowledge of Cost Based Optimization techniques;
- Good knowledge of data pipeline orchestration (e.g. Apache Airflow, Ni-Fi);
- Understanding DataOps and MLOps concepts;
- Experience with agile methodologies in a professional development environment (CI/CD);
- Practical knowledge of Messaging Queue technologies, like Apache Kafka, RabbitMQ;
- Practical knowledge of NoSQL technologies, like Redis, Elasticsearch, Neo4j;
- Practical knowledge about when and what to test (Unit Tests, E2E Tests);
- Problem Solving skills;
- Responsible;
- Experience with RESTful and SOAP APIs.
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