Position: Chief Data Architect
Company: Raiffeisen Bank Aval
Experience required: 5y
Category: Lead
English level: upper
Published: 2021-05-01T00:00:00+03:00

Required skills

The expertise we expect for this role:
• Communication skills
• Must be proficient with DATAHUB solutions/patterns which include ODL(Operational Data Lake), ODS (Operational Data Store) and ADL(Analytic Data Lake)
• Must be proficient with Clouds generally and proficiently build the Cloud-Native solutions and tools to design BigData PaaS/IaaS
• Must be proficient with BigData Processing/Transformation technologies, BigData Storage technologies, BigData Access technologies generally and associated with Cloud technologies specifically
• Must be proficient with Data analysis and synthesis, Data communication, Data governance, Data modeling, Data standards, Data innovation, Metadata management, Problem resolution (data), Strategic thinking (data architecture)
• Turning business problems into data design. You can design data architecture by dealing with problems that span different business areas. You can draw links between problems in order to reach common solutions. You can work across multiple subject areas, a single large or complicated subject area
• Have experience to transform the data as corporate resources into Enterprise with Data Driven Architecture

We offer

•  Join a large international company that provides possibilities for professional and personal growth
• Involve into challenging, large-scale projects which have an impact for our customers
• Knowledge sharing in our Group wide IT community including 14 Raiffeisen Banks
• Flexible working schedule, 28 days of paid vacation, official employment, attractive social package, distant work possibilities
• Competitive salary

Responsibilities

A chief data architect sets the vision for the organization’s use of data as directed by the business goals. At this level, you will:
• Define the technological vision and lead the design of new services or new features and tools
• Determine any necessary services and tool enhancements to meet project needs and ensure the feasibility of these upgrades
• Ensure the coherence, efficiency, scalability, modularity, and compatibility of the features developed by the team
• Analyze and resolve engineering issues pertaining to the services, tools, and/or middleware
• Define the measures required to ensure the data engines optimal performance
• Act as a point of contact for all technical issues on the data services and tools
• Evaluate existing technologies and tools to determine their strengths and weaknesses and recommend those that best meet project objectives and expectations
• Be accountable for the definition of the organization’s data strategy
• Champion data architecture across the organization and set the standards and ways of working for the data architecture community
• Provide advice to project teams and oversee the management of the full data product life cycle and lead the implementation of required solutions
• Have responsibility for making sure that organizations systems are designed in accordance with the data architecture

Project description

Here is the Draft Vision of our Future Data Platform:
The Data Platform is divided into the following distinct parts:
• Core Data Platform
• 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