• Higher education in data analysis, information technology, mathematics, statistics, economics, finance, business informatics or related fields.
• At least 2 years of experience as a Data Analyst, Product Analyst, Web Analyst, Digital Analyst or BI Analyst.
• Strong command of SQL: writing complex queries, combining data from different sources, aggregations, window functions, CTE, data quality control.
• Practical experience working with product and web analytics systems: Google Analytics 4, Google Tag Manager, Microsoft Clarity or similar platforms.
• Experience in developing tracking plans, defining events, event parameters, user properties, and rules for transferring data to analytical systems.
• Understanding the principles of funnel building, conversion calculation, user churn, audience segmentation, and user path analysis.
• Experience creating analytical dashboards and data visualization in Power BI, Looker Studio, Tableau, Qlik Sense or similar tools.
• Skills in working with dataLayer, configuring tags, triggers, variables, and user events in Google Tag Manager.
• Understanding the specifics of tracking user behavior on websites and mobile apps. Application analytics is used to evaluate user actions throughout the user journey.appsflyer
• The ability to verify the correctness of the collection of analytical data, identify errors in the transmission of events and prepare recommendations for their elimination.
• Attention to detail, analytical thinking, and the ability to clearly present analysis results to business customers and technical teams.
• It will be an advantage:

• Experience setting up e-commerce events, payment scenarios, registration, authorization, and user IDs.
• Experience working with mobile analytics: Firebase Analytics, AppMetrica, Amplitude, Mixpanel or similar systems.
• Knowledge of Python, R or other data processing and analysis tools.
• Experience working with databases, DWH, BI-storefronts or product analytics.
• Understanding the principles of personal data protection and the requirements for transferring user identifiers to analytical systems.
• GA4 and Microsoft Clarity integration experience; Clarity can be connected to a GA4 resource for matching user behavior data.

• Higher education in project management, information technology, economics, finance, management, business informatics or related fields.
• At least 3 years of experience as a Project Manager, Project Manager, Delivery Manager or Project Coordinator.
• Experience in managing IT projects, information system implementation projects, system integration, software development or data platforms.
• The ability to form, decompose, prioritize and update the project backlog, taking into account business goals, requirements, deadlines and technical constraints.
• Practical experience in developing and maintaining a project roadmap, calendar plan, project schedule and control points.
• Skills in managing deadlines, resources, dependencies, budget, and project workload.
• Experience coordinating cross-functional teams, including business analysts, developers, data engineers, DevOps engineers, testers, and customer representatives.
• Skills in conducting workshops, status meetings, planning, retrospectives, and presentations of interim results.
• Experience in communicating with customers, key stakeholders, and heads of business units.
• The ability to identify, analyze and control project risks, as well as formulate and implement measures to reduce them.
• Experience in organizing the acceptance of work results, preparing reports and supporting the completion of project stages.
• Ability to work with design, functional and technical documentation.
• Developed communication skills, systematic thinking, independence, responsibility and result orientation.

It will be an advantage:

• Certification in project management: PMP, PRINCE2, PMI-ACP, Scrum Master, AgilePM or similar.
• Experience working on Agile, Scrum, Kanban, Waterfall, or a hybrid project management model.
• Knowledge of project and task management tools: Jira, Confluence, MS Project, Azure DevOps, Trello, Notion or analogues.
• Experience in project management in the field of DWH, integrations, BI, Data Governance, digital transformation or government information systems.
• Skills in preparing managerial, financial and project reports.

• Higher education in the field of information technology, software engineering, information systems, computer engineering, computer science or related technical fields.
• At least 3-5 years of experience as a Technical Architect, Solution Architect, Lead Developer, Tech Lead, Data Architect or Lead Development Engineer.
• Practical experience in designing, developing, and maintaining corporate information systems, integration solutions, data platforms, or DWH.
• Experience in technical leadership of teams of backend developers, Data Engineers, ETL developers or integration engineers.
• A confident understanding of the DWH architecture, Data Lake/Lakehouse approaches, and the principles of organizing Bronze, Silver, and Gold data layers.
• Experience in designing and maintaining ETL/ELT pipelines, data extraction, transformation, and loading processes.
• Knowledge of the principles of integration of information systems: API, REST/SOAP, JSON, XML, message queues, event architectures and data exchange.
• Understanding the principles of designing microservice architecture, distributed systems, high-load services, and fault-tolerant solutions.
• Experience working with relational and/or non-relational databases, strong knowledge of SQL and data modeling principles.
• Knowledge of code quality assurance practices: code review, testing, version control, CI/CD, documentation and technical debt management.
• Understanding non-functional requirements: performance, scalability, security, reliability, fault tolerance, monitoring and logging.
• Experience in preparing architectural and technical documentation: architectural diagrams, technical solutions, API specifications, data models, development standards, and deployment instructions.
• Technical leadership skills, decomposition of complex tasks, making informed decisions and effective communication with business and technical teams.

It will be an advantage:

• Experience working with Kubernetes, Docker, CI/CD pipelines, GitLab CI/CD, Jenkins, Azure DevOps or similar tools.
• Knowledge of Apache Airflow, dbt, Apache Spark, Kafka, Hadoop, Trino, ClickHouse, Greenplum, PostgreSQL, Oracle or similar technologies.
• Experience in implementing Data Governance, Data Quality, Data Lineage, and metadata management practices.
• Knowledge of cloud platforms and services: AWS, Azure, Google Cloud or private cloud solutions.
• Certifications in architecture, cloud technologies, data management, or Agile approaches.
• Experience in building and developing DWH platforms in large organizations or digital transformation projects.

• Higher education in the field of information technology, computer engineering, software engineering, information systems, telecommunications or related technical fields.
• At least 2-3 years of experience as a DevOps engineer, system administrator, infrastructure engineer or SRE engineer.
• Practical experience in the administration of Linux systems and server infrastructure.
• Experience working with Kubernetes, OpenShift, Docker, or similar container platforms.
• Understanding how clusters, network infrastructure, load balancing, data warehouses, and computing resource management work.
• Experience in setting up and maintaining CI/CD pipelines for building, testing, and deploying applications.
• Knowledge of Git version control systems and deployment automation tools.
• Experience working with monitoring, logging, and notification systems: Prometheus, Grafana, ELK/EFK Stack, Zabbix, or analogues.
• Understanding the principles of configuration and secret management, including the secure storage of keys, tokens, passwords, and other credentials.
• Skills in working with databases, data processing platforms, or data warehouses will be an advantage.
• Understanding backup, data recovery, and infrastructure resiliency processes.
• Incident analysis skills, troubleshooting, service recovery, and technical documentation preparation.
• Responsibility, systems thinking, attention to detail, and the ability to interact with developers, data engineers, and analysts.

It will be an advantage:

• Experience in maintaining DWH platforms, Big Data solutions, ETL/ELT processes, or integration services.
• Knowledge of Infrastructure as Code tools: Terraform, Ansible, Helm, Puppet, Chef or analogues.
• Experience working with message brokers and streaming data processing: Kafka, RabbitMQ, ActiveMQ or analogues.
• Knowledge of data storage and processing technologies: PostgreSQL, MS SQL Server, Oracle, ClickHouse, Greenplum, Hadoop, Spark or analogues.
• Experience configuring Kubernetes clusters, Helm charts, Ingress, Service Mesh, network policies, and resource quota management.
• Knowledge of the principles of information security, access management and infrastructure protection.

• Higher education in the field of information technology, software engineering, computer engineering, information systems or related fields.
• At least 2 years of experience as a Backend developer.
• Strong command of one or more programming languages for server-side development: Java, Python, C#, Go, JavaScript/TypeScript or their analogues.
• Experience in the development, maintenance and optimization of backend services and microservice applications.
• Practical experience in API development and support, including REST API; knowledge of SOAP will be an advantage.
• Understanding the principles of integration of information systems, JSON, XML, CSV data exchange formats, and authentication/authorization mechanisms.
• Experience working with relational and/or non-relational databases, strong command of SQL.
• Understanding the principles of DWH, ETL/ELT processes, integration flows, and data transfer between systems.
• Experience working with Git version control systems, build tools, CI/CD, and release management processes.
• Skills in error diagnosis, log analysis, monitoring, and optimizing service performance.
• Ability to maintain technical documentation: description of API, service architecture, integration contracts, settings, and deployment procedures.
• Responsibility, attention to detail, analytical thinking, and willingness to interact with the development team, analysts, and data scientists.

It will be an advantage:

• Experience working with Docker, Kubernetes, and containerized applications.
• Knowledge of message brokers and event integrations: Kafka, RabbitMQ, ActiveMQ or analogues.
• Experience working with API Gateway, authorization services, OAuth 2.0, OpenID Connect, JWT.
• Knowledge of monitoring and logging tools: ELK/EFK Stack, Grafana, Prometheus, Zabbix or analogues.
• Experience developing for data platforms, enterprise data warehouses, or large integration solutions.
• Knowledge of the principles of secure API development and protection.

• Higher education in information technology, information systems, software engineering, applied mathematics, data analysis, or related fields.
• At least 2 years of experience as a Data Engineer, BI developer, Data engineer, ETL developer or data analyst.
• Proficiency in SQL: writing complex queries, optimization, working with large amounts of data, window functions, CTE and procedures.
• Practical experience in the development, formation and maintenance of data Marts.
• Understanding the architecture of data warehouses and the principles of organizing data layers, including Bronze/Silver/Gold or similar approaches.
• Experience in building and maintaining ETL/ELT processes, uploading, converting, and updating data.
• Understanding data models: normalized models, "star", "snowflake", fact and measurement tables.
• Skills in analyzing the quality, completeness, consistency, and relevance of data.
• Experience in maintaining technical documentation on data structures, sources, transformations, and rules for creating storefronts.
• Attention to detail, analytical thinking, responsibility and teamwork skills.

It will be an advantage:

• Experience working with data orchestration and processing tools: Apache Airflow, dbt, Apache Spark, Kafka or similar.
• Knowledge of Python, PySpark or other languages and tools for data processing.
• Experience working with modern databases and data platforms: PostgreSQL, MS SQL Server, Oracle, ClickHouse, Greenplum, BigQuery, Snowflake or their analogues.
• Knowledge of Git, CI/CD approaches and principles of version control.
• Work experience in data warehousing, BI-reporting, or digital transformation projects.

• Higher education in Information Technology, Business Informatics, Economics, Finance, Management, or a related field.
• At least 2 years of experience as a Business Analyst, Systems Analyst, or Integration Solutions Analyst.
• Experience in gathering, analysing, documenting, and coordinating business and functional requirements.
• Understanding of information-system integration principles, including APIs, REST/SOAP, JSON, XML, message queues, and file-based data exchange.
• Skills in preparing project and technical documentation, including business requirements, functional requirements, technical specifications, integration specifications, and user scenarios.
• Ability to model business processes and describe system interaction scenarios.
• Experience in preparing tasks for development teams, supporting task delivery, and participating in acceptance of deliverables.
• Skills in developing role and access-rights matrices, with an understanding of user access-control principles.
• Ability to work with large volumes of data and develop and maintain data registers.
• Strong written and verbal communication skills, attention to detail, structured thinking, and the ability to communicate effectively with business stakeholders and technical specialists.

Will be considered an advantage:

• Experience with government information systems, corporate platforms, or large-scale integration projects.
• Knowledge of BPMN, UML, SQL, and requirements/task-management tools such as Jira, Confluence, or similar platforms.
• Experience in digital-transformation projects, information-system implementation, or data-warehouse development.

Higher or incomplete higher education (IT, economics, management, business analysis or related fields);

Basic understanding of business analysis processes and software development lifecycle;

Ability to collect and structure information;

Skills of working with Excel/Google Sheets, PowerPoint/Google Slides;

Good oral and written communication;

Analytical thinking and attention to detail;

It will be a plus: knowledge of BPMN/UML, experience writing requirements, participation in educational or pet projects

- Experience working with technological startup projects and understanding the specifics of solutions in the field of Smart City and artificial intelligence - at least 2 years.

- Practical skills in tracking and mentoring startup teams at different stages of development.

- Experience in conducting strategic sessions, foresight sessions, or strategic planning for project teams.

- Experience in public speaking, event moderation, and presentation sessions (Demo Day, pitch sessions).

- The ability to build an individual development trajectory for each team, taking into account its specifics.

- Communication skills with different audiences, from novice startups to representatives of working groups and the expert community.

- Higher education in information technology, data analysis, applied mathematics, computer science or related fields, or international certifications in Data Analytics, Big Data, Machine Learning and Generative AI (NVIDIA, Google, AWS, Microsoft, Databricks, DeepLearning.AI , Anthropic, OpenAI or similar).

- Practical work experience in the field of data analytics, Big Data, Data Science or Machine Learning for at least 5 years.

- Experience in implementing data analysis, ML and AI projects using AWS, Microsoft Azure, Google Cloud Platform or similar technologies.

- Proficiency in Python (Pandas, NumPy, Scikit-learn, Jupyter Notebook), SQL, and modern data analysis tools.

- Practical experience working with Big Data technologies (Apache Spark, Hadoop, Hive, Databricks or similar).

- Experience in building analytical models, visualizing data, and developing machine learning-based solutions.

- Practical experience in using modern AI tools and generative AI to automate analytical processes.

- At least 1 year of experience in the development and implementation of educational programs in the field of data analytics, Big Data, ML or AI.

- At least 1 year of training experience for employees of government agencies, the corporate sector, educational organizations or students.

- Experience in conducting workshops, intensive courses, professional development programs or corporate training.

- The advantage will be: presentations at international conferences on AI/Data Science/ML/Big Data; availability of publications in international scientific journals or peer-reviewed publications in the fields of Data Science, ML or AI.

- Project support skills, project expert assessment and technical mentoring.