Position: Data engineer/Solution Architect
Company: Raiffeisen Bank Aval
Category: Lead
Experience required: 1y
English level: upper
Published: 2021-04-01T00:00:00+03:00

The expertise is needed: 

•	DATAHUB solutions/patterns which include ODL(Operational Data Lake), ODS (Operational Data Store) and ADL(Analytic Data Lake). 
•	Clouds generally and proficiently build the Cloud-Native solutions and tools to design BigData PaaS/IaaS. 
•	BigData Ingestion technologies generally and associated with Cloud technologies specifically.  
•	BigData Processing/Transformation technologies generally and associated with Cloud technologies specifically.  
•	BigData Storage technologies generally and associated with Cloud technologies specifically.  
•	BigData Access technologies generally and associated with Cloud technologies specifically.  
•	BigData technologies generally and associated with Cloud technologies specifically.  
•	Data communication. You can turn complex data into clear, simple, and actionable stories. You will share data communication skills with the team and across the government. 
•	Data innovation. You can identify areas of innovation in data tools and techniques and recognize appropriate timing for adoption. 
•	Data modeling. You understand the concepts and principles of data modeling and can produce relevant data models across multiple subject areas. You know how to reverse-engineer data models from a live system. You understand industry-recognized data modeling patterns and standards and know when to apply them. You can compare and align different data models. 
 
Here is the Draft Vision of our Future Data Platform: 

•	The Data Platform is divided into the following distinct parts: 
o	Core Data Platform 
o	Onboarded Data Producer/Consumer Applications, Configuration & Customisations 
•	Onboarding & Management of Data Producer/Consumer Applications 
•	Application, Data Source, Job, Job Data, Job Steps, and Data Access Taxonomies 
•	Standardized Push/Pull Streaming Ingestion Interfaces 
•	Standardized Push/Pull Batch Ingestion Interfaces 
•	Polyglot Data-lake Storage (e.g., Bucket, KV, NoSQL, Search, Warehouse, SQL, etc.) 
•	Customizable Ingestion Conformance-tier Processors 
•	Customizable Ingestion Stage Processors 
•	Customizable Ingestion Archive Processors 
•	Customizable Ingestion Optimised Format (e.g., Parquet/ORC) Processors 
•	Customizable Transformation/Enrichment Processors 
•	Customizable Microservices & API Processors 
•	Standardized Query API (e.g., J/ODBC) Data Access Interfaces 
•	Standardized Export API, Bucket Endpoint & Notify Data Access Interfaces 
•	Standardized Streaming Egress Data Access Interface 
•	RBAC (Role-Based Access Controls) 
•	Secrets/Vault capabilities 
•	TLS (in-flight) & TDE (at-rest) Encryption capabilities 
•	Operational Metrics & Monitoring capabilities 
•	Data Platform Resource Utilisation Tracking & Cost Allocation capabilities 
•	DLM, Archive, Retention capabilities 
•	Schema Registry capabilities 
•	Login & Data Platform Portal Home UI 
•	Analytics Notebook UI (e.g., Jupiter) 
•	Data Catalog UI 
•	VDI Workbench Portal UI 
•	Job Management UI 
•	Administration UI