Chief Data Architect (вакансія неактивна)

The expertise we expect for this role:
• Must be able to speak directly to the business representatives and engage in dialog. Communication skills — you can mediate between people and mend relationships, communicating with stakeholders at all levels. You can manage stakeholders’ expectations and facilitate discussions across high risk or complexity or under constrained timescales. You know how to speak on behalf of the community to large audiences.
• 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 Ingestion technologies generally and associated with Cloud technologies specifically.
• Must be proficient with BigData Processing/Transformation technologies generally and associated with Cloud technologies specifically.
• Must be proficient with BigData Storage technologies generally and associated with Cloud technologies specifically.
• Must be proficient with BigData Access technologies generally and associated with Cloud technologies specifically.
• Must be proficient with BigData technologies generally and associated with Cloud technologies specifically.
• Data analysis and synthesis. You can undertake data profiling and source system analysis. You can present clear insights to colleagues to support the end-use of the data. Increase the ability of knowledge workers to transform data into information.
• 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 governance. You can ensure data governance supports changes to the organizational strategy. You can align data governance with broader governance (for example, budget). You know how to assure and integrate data services to meet the needs of multiple business services. You work proactively to ensure the organization designs architecture that considers data.
• 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.
• Data standards. You develop and set data standards for an organization. You can communicate the business benefit of data standards, champion and govern those standards across the organization. You understand where standards need to be set across an organization. You can act as the escalation point for breaches of data standards and make recommendations about how the organization should resolve that breach.
• Metadata management. You understand how metadata repositories can support different areas of the business. You promote and communicate the value of metadata repositories. You set up robust governance processes for keeping the repositories up to date. You understand a range of tools for storing and working with metadata. You can provide oversight and advice to more inexperienced members of the team.
• Problem resolution (data). You can anticipate problems and know how to prevent them. You understand how the problem fits into the larger picture. You can articulate the problem and help others to communicate the problem. You can ensure that the most appropriate actions are taken to resolve issues as they occur. You coordinate teams to resolve problems and implement solutions and preventative measures.
• Strategic thinking (data architecture). You can leads the design and implementation of data strategy, directing the evaluation of strategies and policies to ensure business requirements are being met.
• 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.

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 when current options do not meet business needs;
• 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;
• In collaboration with the technical directors, communicate the technical constraints of the engines and tools to team members to inform them on production options and related best practices;
• 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;
• With the technical directors and in keeping with technical constraints, ensure that project teams (graphic design, animation, etc.) have the tools required to produce content;
• Evaluate existing technologies and tools to determine their strengths and weaknesses and recommend those that best meet project objectives and expectations;
• Anticipate technological advances, understand the issues brought about by new hardware, and implement software systems that support these changes and possibilities;
• Oversee the design of multiple data models and have a broad understanding of how each model fulfills the needs of the business
• 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
• Carry out all other related tasks.

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