Jobs
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Β· 52 views Β· 8 applications Β· 3d
Product Analyst
Full Remote Β· Countries of Europe or Ukraine Β· Product Β· 2 years of experience Β· B1 - IntermediateAt Promova, weβre redefining language education to make it accessible, personal, and effective for todayβs fast-paced world. Our growing team of 170+ professionals is on a mission to connect people, bridge cultures, and empower lifelong learners β...At Promova, weβre redefining language education to make it accessible, personal, and effective for todayβs fast-paced world. Our growing team of 170+ professionals is on a mission to connect people, bridge cultures, and empower lifelong learners β reaching every country except aggressor states (yes, even Antarctica).
We blend AI-driven innovation with human expertise to create tools that help people speak with confidence, embrace new cultures, and truly belong in any language. As part of our team, youβll make a real impact, work in an environment built on care, quality, and creativity, and grow alongside a community that values progress.
With flexible work options, comprehensive benefits, and endless growth opportunities, Promova is more than a workplace β itβs a movement.
Weβre looking for a Product Analyst to join our team and help us in shaping the future of our product by transforming data into actionable insights.
In this high-impact role, youβll take part in analyzing user behavior, building insightful dashboards, and identifying growth opportunities through data. You'll have a direct chance to influence product and business decisions, and to optimize and scale our existing analytics infrastructure.
This Role Is For You If You Want To:
- Influence Product Direction: generate and validate product hypotheses, and make decisions that directly influence the further development of the product.
- Work with Real User Data: gain a deep understanding of user motivations and barriers, conduct research that directly improves the user experience.
- Analyze Big Data Volumes: work with massive datasetsβ our application is used by hundreds of thousands of users every month.
What Youβll Do:
- A/B Test Analysis: interpret the results of A/B tests and provide clear, data-driven recommendations for product development.
- User Research: perform in-depth research on in-product user behavior to uncover key patterns and insights.
- Data Visualization: create and maintain analytical reports and dashboards using Tableau and Amplitude.
- Data Quality: actively contribute to monitoring and improving the quality and reliability of product data and tracking.
What Weβre Looking For
- 2+ years of experience as a Product Analyst.
- Strong SQL skills for database management and analysis of large datasets.
- Experience working with data visualization tools such as Tableau and Amplitude.
- Proven experience in conducting A/B tests and analyzing results.
- English proficiency B1+.
Will Be a Plus:
- Hands-on experience with data analysis in Python.
Corporate benefits:
π Growth β offered to help develop your skills, advance your career, and reach your full potential: compensation for additional training at external events and seminars; access to a large electronic library; paid online courses and conferences; Promova English Group; English Classes; Promova Speaking Club, and access to Promova Premium.
π§πΌWellbeing β offered to support your overall health, happiness, and resilience: work remotely from any safe location worldwide; flexible work schedule; 20 paid vacation days per year; unlimited number of sick days, medical insurance coverage; mental health support; power station reimbursement; employee discounts and special benefits for remote employees.
ππΌββοΈ Fun & Activities β offered to foster informal communication and strengthen social connections among teammates: remote team compensation for gathering and team-building episodes.
Interview Process:
- Pre-screen with Recruiter
- Interview with Product Analyst Team Lead
- Technical & Case Interview
- Bar-raising
If you're passionate about data-driven decision-making and eager to shape the future of language learning, weβd love to hear from you!
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Β· 15 views Β· 0 applications Β· 3d
Functional Analyst β MS Finance and Operations
Hybrid Remote Β· Ukraine (Kyiv) Β· Product Β· 5 years of experience Β· B2 - Upper IntermediateWe are looking for a Functional Analyst for the Microsoft Dynamics 365 Finance and Operations platform to help transform the companyβs financial and operational processes using modern technologies. You will join a cross-functional team working on the...We are looking for a Functional Analyst for the Microsoft Dynamics 365 Finance and Operations platform to help transform the companyβs financial and operational processes using modern technologies. You will join a cross-functional team working on the implementation and optimization of business solutions in the field of finance, logistics, and resource management. If you have experience working with D365 F&O and strive to influence strategic processes, this role is for you.
What you will do
- Gather information from and collaborate with different types of stakeholders (finance, procurement, warehouse, IT)
- Understand strategic business needs and plans for growth
- Gather and document detailed business requirements and transform them into user stories, including acceptance criteria
- Create, document, and maintain solution designs
- Execute standard and advanced configuration of the system, giving demos/prototypes to business users
- Prepare functional gap design documents
- Test new configurations and customizations β ensuring the provided functionality is in line with existing flows and satisfies stakeholdersβ needs and requirements
- Organize key user validation process, support for end-to-end user acceptance testing
- Usersβ consultancy and support; handle tickets as a second-level support engineer
- Follow the Change and Release management process
- Prepare release notes
- Manage tasks (AzureDevOps/Jira)
Your profile
- Upper-intermediate English
- >3 yearsβ experience with Microsoft Dynamics 365 Finance&Operations implementation and support
- Extensive experience in Microsoft Dynamics 365 Finance&Operations implementation projects
- Strong knowledge of standard D365 functionalities and most of the business processes listed below:β―
- Accounting policy (General Ledger, account structure, period close, etc.)
- Accounts payable
- Accounts receivable
- Manufacturing accounting
- Inventory accounting (closing and adjustment, inventory revaluation, inventory counting, inventory posting etc.)
- Cost accounting
- Tax accounting (understanding of business process flows)
- Subscription billing (nice to have)
- Electronic reporting
- Experience in supply chain management flows is a plus
- Experience working in an integrated environment (and understanding of the approach of working with it)
- Experience with AzureDevops/Jira
- UML/BPMN knowledge is a plus
- Experience in preparing user stories, user manuals, and release notes
- Able to adapt requirements to both technical and business languages
- Experience with the preparation of different types of products and project documentation
- Experience with organizing validation activities (user acceptance testing)
- A technical background is an advantage
- Logical and analytical thinkingβ―
- Independent research on solutions
- A critical thinker, detail-oriented, and self-organized
Please note that we work according to the hybrid way of work with the office in Kyiv.
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Β· 34 views Β· 8 applications Β· 3d
Data Analytics Specialist
Full Remote Β· Worldwide Β· 5 years of experience Β· B2 - Upper IntermediateLocation: Remotely Employment Type: Full-time Project for a Canadian government, EST working hours. Role Overview The Data Analytics Specialist is responsible for leading the design, development, and delivery of analytics solutions that enable...Location: Remotely
Employment Type: Full-timeProject for a Canadian government, EST working hours.
Role Overview
The Data Analytics Specialist is responsible for leading the design, development, and delivery of analytics solutions that enable evidence-based decision-making and generate actionable insights for the Ministry. This role will collaborate closely with subject matter experts (SMEs) and stakeholders to assess current analytics capabilities, define future requirements, and develop robust data models and reports that support strategic and operational goals.
Key Responsibilities
- Lead the development and delivery of functional and ministry-specific analytics to support evidence-based decision-making and provide actionable insights.
- Collaborate with Ministry SMEs to assess current analytics and reporting capabilities, gather requirements for the future state, and identify opportunities for improvement.
- Own the end-to-end execution of analytics requirements, including dataset preparation, report development, and dashboard delivery.
- Participate in documentation, development, testing, and end-user training related to analytics solutions.
- Work with functional experts and stakeholders to analyze complex business challenges and design appropriate Business Intelligence (BI) and data analytics solutions.
- Design and implement methods for capturing, structuring, transforming, and processing data to support analytical and predictive models.
- Develop and maintain data models that provide accurate, meaningful, and unbiased insights for decision support.
- Provide expert interpretation and advisory support to client groups and stakeholders, helping to translate analytics into actionable recommendations and proactive insights.
- Ensure that analytics outputs are aligned with organizational goals, governance frameworks, and data quality standards.
- Contribute to continuous improvement initiatives by identifying new opportunities for automation, optimization, and advanced analytics use cases.
Qualifications & Experience
- Bachelorβs degree in Data Science, Computer Science, Statistics, Mathematics, or a related field (or equivalent professional experience).
- 5+ years of experience in data analytics, business intelligence, or data modeling, preferably in large or complex organizations.
- Proven experience with BI tools (e.g., Power BI, Tableau, Qlik) and data transformation frameworks (e.g., SQL, Python, R).
- Strong understanding of data warehousing, ETL processes, and data visualization best practices.
- Excellent analytical, problem-solving, and communication skills, with the ability to interpret complex data and communicate insights to non-technical stakeholders.
- Familiarity with public sector or enterprise-level analytics environments is an asset.
- Experience working within structured project delivery frameworks (e.g., Agile or Waterfall) is preferred.
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Β· 35 views Β· 8 applications Β· 3d
Data Analyst (Gambling Experience is a Must)
Full Remote Β· Worldwide Β· Product Β· 3 years of experience Β· B1 - IntermediateWe are looking for an experienced Data Analyst with a strong background in the gambling industry and a solid understanding of product and performance metrics. Your insights will directly support product, marketing, and business decisions. Requirements ...We are looking for an experienced Data Analyst with a strong background in the gambling industry and a solid understanding of product and performance metrics. Your insights will directly support product, marketing, and business decisions.
Requirements
- Mandatory experience in the gambling or iGaming industry
- 3+ years of experience in data analytics, preferably within iGaming or related digital products;
- Strong SQL skills;
- Hands-on experience with Python for analytics, automation, and data processing;
- Deep understanding of key iGaming metrics (LTV, ARPU/ARPPU, Retention, Churn, Conversion, RTP, GGR/NGR, etc.);
- Experience working with BI tools (Tableau/Power BI/Looker; Tableau is a strong advantage);
- Proven ability to work with large datasets and build structured reports;
- Strong analytical mindset and the ability to generate clear, actionable insights.
Key Responsibilities
- Build and maintain dashboards and reports for product, marketing, and business teams;
- Analyze user behavior, funnels, retention, and overall product performance;
- Assess the effectiveness of marketing channels, campaigns, and traffic quality;
- Provide analytics to support strategic and operational decision-making;
- Automate recurring reports and optimize data processes;
- Monitor key product and business metrics, identify anomalies, and propose solutions.
Nice to Have
- Experience in Data Engineering (ETL, pipeline optimization);
- Experience working with APIs, integrations, and automation;
- Background in user behavior modeling and metric forecasting.
What We Offer: - Work from anywhere: full remote flexibility or the option to work from our office;
- Flexible working hours so you can stay productive while maintaining work-life balance;
- Growth opportunities: as we scale, youβll have space to develop your career and grow into a strategic leadership role;
If this sounds like you β weβd love to see your CV!
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We value initiative, support bold ideas, and believe in working as a team. -
Β· 23 views Β· 6 applications Β· 3d
Senior Data Migration Specialist
Full Remote Β· Worldwide Β· 4.5 years of experience Β· B2 - Upper IntermediateLocation: Remotely Employment Type: Full-time Project for a Canadian government, EST working hours. Role Overview The Senior Data Migration Specialist is responsible for planning, executing, and overseeing all data migration activities required for the...Location: Remotely
Employment Type: Full-timeProject for a Canadian government, EST working hours.
Role Overview
The Senior Data Migration Specialist is responsible for planning, executing, and overseeing all data migration activities required for the successful transition from legacy systems to the new Solution. This role ensures that data is accurately extracted, transformed, validated, and loaded in accordance with project goals and data governance standards. The Specialist will work closely with technical teams, business stakeholders, and subject matter experts to ensure a seamless and high-quality migration process.
Key Responsibilities
- Assess source and target systems to understand data structures, relationships, formats, and dependencies.
- Collaborate with stakeholders to define data migration requirements, objectives, and scope.
- Develop comprehensive data migration strategies, plans, and timelines that align with overall project milestones.
- Extract data from legacy systems, databases, and applications using appropriate tools and methodologies.
- Transform and cleanse data to ensure compatibility with the target Solutionβs structure, format, and standards.
- Load data into the new system while maintaining integrity, accuracy, and consistency.
- Validate migrated data to ensure completeness, accuracy, and compliance with requirements.
- Conduct reconciliation between the source and target systems to confirm successful migration.
- Develop and execute detailed test plans to verify data quality and system functionality post-migration.
- Identify, troubleshoot, and resolve issues related to data discrepancies, performance, or system compatibility.
- Document migration processes, data mappings, scripts, and configurations for audit and knowledge transfer purposes.
- Prepare and deliver reports on migration progress, issues, risks, and outcomes to project leadership and stakeholders.
Qualifications & Experience
- Bachelorβs degree in Computer Science, Information Systems, or a related field (or equivalent professional experience).
- 5 years of experience in data migration, data integration, or database management
- Proven expertise in ETL (Extract, Transform, Load) processes, tools, and methodologies.
- Strong hands-on experience with SQL, data transformation scripts, and data quality assurance techniques.
- Familiarity with enterprise data migration projects, especially involving ERP, CRM, or large-scale information systems.
- Deep understanding of data validation, reconciliation, and testing procedures.
- Excellent analytical, problem-solving, and documentation skills.
- Experience collaborating with cross-functional teams in complex, multi-system environments.
- Knowledge of cloud migration tools or platforms (e.g., Azure Data Factory, AWS Glue, Informatica) is an asset.
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Β· 20 views Β· 1 application Β· 2d
Data Analyst for WebPros
Full Remote Β· Ukraine Β· 3.5 years of experience Β· B2 - Upper IntermediateOur client WebPros, the largest web hosting software and automation company, manages 900,000+ servers, 85 million domains, and 33 million users. WebPros unites top providers in web hosting, billing automation, infrastructure, server management, and online...Our client
WebPros, the largest web hosting software and automation company, manages 900,000+ servers, 85 million domains, and 33 million users. WebPros unites top providers in web hosting, billing automation, infrastructure, server management, and online marketing software. Currently, their lineup includes cPanel, Plesk, SolusVM, WHMCS, XOVI NOW, Sitejet, 360 Monitoring, and koality, with ongoing additions.
Job Description
Join our global Data&AI team at WebPros, where you will play an important role in transforming data into actionable insights. As a Data Analyst, you will work closely with cross-functional teams to understand their data needs and deliver effective data solutions. Your expertise will help drive data-driven decision-making and enhance our business operations.
Responsibilities
As a Data Analyst, your key responsibilities will include:
Β· Response to data analytics requests from various stakeholders (C-level, Go-To-Market, Product, Finance)
Β· Analyze and interpret complex data sets to identify trends, patterns, and insights.
Β· Create and maintain dashboards and reports using BI tools like Google Looker Studio.
Β· Collaborate with stakeholders to understand their data requirements and provide actionable insights.
Β· Design and create data visualizations to effectively communicate insights and trends to stakeholders.
Qualifications
To be successful in this role, candidates should have:
Β· Proficiency in SQL for data querying and manipulation.
Β· Strong knowledge of BI tools like Google Looker Studio or Tableau.
Β· Excellent problem-solving skills and attention to detail.
Β· Exceptional communication and collaboration abilities.
Β· Familiarity with cloud operations in AWS or GCP is a plus.
Β· Experience with Python coding, including libraries such as numpy and pandas is a plus.
Β· Knowledge of the hosting / internet industry would be a plus.
Q&ADoes the job come with a probation period?
Yes, there is a 3-month probation period.
What is the expected work schedule?
Full-time, flexible. You can work remotely or choose a hybrid mode (on-site in the Lviv office + remote).
Social package & benefits:
- Full medical insurance
- MacBook & accessories
- English lessons- Accountant assistance
- Minimal bureaucracy, synergy, and formalities, primarily focusing on effective communication
Hiring process:
- Screening call with Recruiter (soft skills interview) ~ 20 min
- Technical interview with the Tech Expert from Webpros ~ 60 min
- Final interview with Manager from Webpros ~ 60 min
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Β· 25 views Β· 3 applications Β· 2d
Technical Writer + Business Analyst
Full Remote Β· Ukraine Β· 3 years of experience Β· B2 - Upper IntermediateDiya is going through a period of steady growth and we are currently looking for a new team member to join our technical team. If you are passionate about technical things and have both theoretical and practical skills, and are looking for further...Diya is going through a period of steady growth and we are currently looking for a new team member to join our technical team.
If you are passionate about technical things and have both theoretical and practical skills, and are looking for further development, we encourage you to send us your CV. This position will not be limited to technical tasks. It also involves a lot of communication in English. That is why we expect the candidate to have an appropriate level of English.
We are a successful Ukrainian IT company that provides a full range of IT solutions for small and medium-sized businesses around the world. Our company has extensive professional experience in providing remote technical support services to companies from various industries, helping them to provide excellent customer experience.
Diya is currently looking for a Technical Writer for a full-time position, who is tech-savvy with excellent English skills to join us.
The position is intended for a specialist who already has a technical background and wants to develop not only as a technical writer, but also in the direction of Business Analysis.
Responsibilities for Technical Writer include but are not limited to the following:
- Create, edit, and maintain clear, concise, and accurate technical documentation.
- Translate complex technical information into easy-to-understand content for a variety of audiences.
- Collaborate with engineers to gather information and ensure documentation is complete and accurate.
- Update existing documentation to align with new product features or changes.
Qualifications:
- 2+ years of experience as a Technical Writer
- Excellent written English skills (grammar, spelling, clarity, and style).
- Experience working with technical teams
- Ability to work independently and manage time effectively
- Attention to details and a commitment to delivering high-quality work.
- Ability to structure information and build information architecture for large sections or individual documents.
What we offer:
Comfortable work environment, remote work.
Competitive salary.
Paid vacation and sick leave.
Healthcare insurance and gym.
Training and useful experience.
Work in a young and friendly team.
Career opportunities and professional growth.
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Β· 60 views Β· 2 applications Β· 9d
DWH, SQL developer/Data analyst
Office Work Β· Ukraine (Kyiv) Β· Product Β· 1 year of experience Β· B1 - IntermediateΠΠ’ Β«ΠΡΠΎΠΡΠ΅Π΄ΠΈΡ ΠΠ°Π½ΠΊΒ» - ΡΠΏΠ΅ΡΡΠ°Π»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠΉ Π±Π°Π½ΠΊ Π΄Π»Ρ Π±ΡΠ·Π½Π΅ΡΡ, ΡΠΎ Π²Ρ ΠΎΠ΄ΠΈΡΡ Π΄ΠΎ ΠΌΡΠΆΠ½Π°ΡΠΎΠ΄Π½ΠΎΡ Π³ΡΡΠΏΠΈ ΠΡΠΎΠΡΠ΅Π΄ΠΈΡ, Π°ΠΊΡΡΠΎΠ½Π΅ΡΠΎΠΌ ΡΠΊΠΎΡ Ρ ΠΌΡΠΆΠ½Π°ΡΠΎΠ΄Π½Π° ΡΡΠ½Π°Π½ΡΠΎΠ²Π° ΠΎΡΠ³Π°Π½ΡΠ·Π°ΡΡΡ - ΠΡΠΎΠΡΠ΅Π΄ΠΈΡ Π₯ΠΎΠ»Π΄ΠΈΠ½Π³ (ΠΡΠΌΠ΅ΡΡΠΈΠ½Π°), Π·Π°ΠΏΡΠΎΡΡΡ ΠΏΡΠΈΡΠ΄Π½Π°ΡΠΈΡΡ Π΄ΠΎ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ² ΡΠ° ΠΎΠ³ΠΎΠ»ΠΎΡΡΡ ΠΊΠΎΠ½ΠΊΡΡΡ Π½Π°...ΠΠ’ Β«ΠΡΠΎΠΡΠ΅Π΄ΠΈΡ ΠΠ°Π½ΠΊΒ» - ΡΠΏΠ΅ΡΡΠ°Π»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠΉ Π±Π°Π½ΠΊ Π΄Π»Ρ Π±ΡΠ·Π½Π΅ΡΡ, ΡΠΎ Π²Ρ ΠΎΠ΄ΠΈΡΡ Π΄ΠΎ ΠΌΡΠΆΠ½Π°ΡΠΎΠ΄Π½ΠΎΡ Π³ΡΡΠΏΠΈ ΠΡΠΎΠΡΠ΅Π΄ΠΈΡ, Π°ΠΊΡΡΠΎΠ½Π΅ΡΠΎΠΌ ΡΠΊΠΎΡ Ρ ΠΌΡΠΆΠ½Π°ΡΠΎΠ΄Π½Π° ΡΡΠ½Π°Π½ΡΠΎΠ²Π° ΠΎΡΠ³Π°Π½ΡΠ·Π°ΡΡΡ - ΠΡΠΎΠΡΠ΅Π΄ΠΈΡ Π₯ΠΎΠ»Π΄ΠΈΠ½Π³ (ΠΡΠΌΠ΅ΡΡΠΈΠ½Π°), Π·Π°ΠΏΡΠΎΡΡΡ ΠΏΡΠΈΡΠ΄Π½Π°ΡΠΈΡΡ Π΄ΠΎ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ² ΡΠ° ΠΎΠ³ΠΎΠ»ΠΎΡΡΡ ΠΊΠΎΠ½ΠΊΡΡΡ Π½Π° ΠΏΠΎΡΠ°Π΄Ρ Π°Π½Π°Π»ΡΡΠΈΠΊΠ° ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ Π² ΠΌΡΡΡΡ ΠΠΈΡΠ².
ΠΠΎΠ½Π° Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Π»ΡΠ½ΠΎΡΡΡ:
- ΠΠΈΡΠ°ΡΠΈ, Π·ΠΌΡΠ½ΡΠ²Π°ΡΠΈ ΠΉ ΠΎΠΏΡΠΈΠΌΡΠ·ΠΎΠ²ΡΠ²Π°ΡΠΈ SQL-Π·Π°ΠΏΠΈΡΠΈ, Π·Π±Π΅ΡΠ΅ΠΆΠ΅Π½Ρ ΠΏΡΠΎΡΠ΅Π΄ΡΡΠΈ, ΡΡΠ½ΠΊΡΡΡ ΡΠ° ΡΡΠΈΠ³Π΅ΡΠΈ;
- ΠΠΈΡΡΡΡΠ²Π°ΡΠΈ ΠΏΡΠΎΠ±Π»Π΅ΠΌΠΈ ΡΠ° ΡΡΡΠ½Π΅Π½Π½Ρ Π½Π΅ΠΏΠΎΠ»Π°Π΄ΠΎΠΊ Ρ Π±Π°Π·Ρ Π΄Π°Π½ΠΈΡ ;
- ΠΡΠ΄ΡΡΠΈΠΌΠΊΠ° ΡΠ° Π°Π΄ΠΌΡΠ½ΡΡΡΡΡΠ²Π°Π½Π½Ρ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΡ OLAP-ΠΊΡΠ±ΡΠ²;
- Π‘ΡΠ²ΠΎΡΠ΅Π½Π½Ρ, Π°Π΄ΠΌΡΠ½ΡΡΡΡΡΠ²Π°Π½Π½Ρ ΡΠ° ΠΎΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡ Π·Π²ΡΡΡΠ² Ρ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΠ°Ρ Π½Π° Π±Π°Π·Ρ SSRS.
- ΠΡΠΎΠ΅ΠΊΡΡΠ²Π°Π½Π½Ρ Π²ΡΡΡΠΈΠ½ Π΄Π°Π½ΠΈΡ ΡΠ° ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ° Π΄ΠΈΠ½Π°ΠΌΡΡΠ½ΠΈΡ Π²ΡΠ·ΡΠ°Π»ΡΠ·Π°ΡΡΠΉ Π² Power BI, ΡΠΊΡ Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°ΡΡΡ ΠΏΡΠΈΠΉΠΌΠ°ΡΠΈ ΡΡΡΠ΅Π½Π½Ρ (Π±ΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ);
- ΠΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° ΡΠ° Π²Π΅Π΄Π΅Π½Π½Ρ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡ Π΄Π»Ρ Π½ΠΎΠ²ΠΈΡ ΡΠΎΠ·ΡΠΎΠ±ΠΎΠΊ ΡΠ° ΡΠΈΡΡΠ΅ΠΌ. ΠΠ°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½Π½Ρ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎΡΡΡ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡ Π΄Π»Ρ Π²Π½Π΅ΡΠ΅Π½ΠΈΡ Π·ΠΌΡΠ½.ΠΠ½Π°Π½Π½Ρ ΡΠ° Π΄ΠΎΡΠ²ΡΠ΄ ΠΏΡΠ°ΠΊΡΠΈΡΠ½ΠΎΠ³ΠΎ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ:
- Π ΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈ ΡΠ° ΠΏΡΠ΄ΡΡΠΈΠΌΡΠ²Π°ΡΠΈ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Π΅ ΡΡ ΠΎΠ²ΠΈΡΠ΅ Π΄Π°Π½ΠΈΡ (DWH) Ρ ETL-ΠΏΡΠΎΡΠ΅ΡΠΈ Π½Π° Π±Π°Π·Ρ MS SQL Server;
- MS SQL Server (T-SQL);
- ETL;
- MS Visual Studio ( SSIS/SSAS/SSRS );
- ΠΠΎΡΠ²ΡΠ΄ Ρ ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ DAX-Π²ΠΈΡΠ°Π·ΡΠ² (ΠΎΠ±ΡΠΈΡΠ»Π΅Π½Π½Ρ, KPI, ΠΌΡΡΠΈ, calculated columns) (Π±ΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ).
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Β· 47 views Β· 4 applications Β· 6d
Data Analyst (advanced Ρommercial Π°nalytics)
Full Remote Β· Countries of Europe or Ukraine Β· Product Β· 3 years of experience Β· B1 - Intermediate Ukrainian Product πΊπ¦ΠΠΈ β E-Com β ΠΊΠΎΠΌΠ°Π½Π΄Π° Π·Π°ΠΊΠΎΡ Π°Π½ΠΈΡ Ρ Foodtech ΡΠ° ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΈΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡ. Π ΠΌΠΈ ΡΡΠΊΠ°ΡΠΌΠΎ Data Analyst, ΡΠΊΠΈΠΉ Π°Π±ΠΎ ΡΠΊΠ° ΡΠ°Π·ΠΎΠΌ Π· Π½Π°ΠΌΠΈ Π³ΠΎΡΠΎΠ²ΠΈΠΉ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈΡΡ, Π²ΡΠΈΡΠΈΡΡ ΡΠ° Π²ΡΠΈΡΠΈ. Π ΡΠ΅ β ΠΌΠΈ Π»Π°ΠΌΠ°ΡΠΌΠΎ ΡΡΠ΅ΡΠ΅ΠΎΡΠΈΠΏΠΈ, ΡΠΎ ΡΠΈΡΠ΅ΠΉΠ» β ΡΠΎ Π»ΠΈΡΠ΅ ΠΏΡΠΎ ΠΏΠΎΠΌΡΠ΄ΠΎΡΡΠΈΠΊΠΈ. ΠΠΎΠ²ΡΡ, ΡΠ΅Ρ Π½ΡΡΠ½Π° ΡΠ°ΡΡΠΈΠ½Π°...ΠΠΈ β E-Com β ΠΊΠΎΠΌΠ°Π½Π΄Π° Π·Π°ΠΊΠΎΡ Π°Π½ΠΈΡ Ρ Foodtech ΡΠ° ΡΠΊΡΠ°ΡΠ½ΡΡΠΊΠΈΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡ.
Π ΠΌΠΈ ΡΡΠΊΠ°ΡΠΌΠΎ Data Analyst, ΡΠΊΠΈΠΉ Π°Π±ΠΎ ΡΠΊΠ° ΡΠ°Π·ΠΎΠΌ Π· Π½Π°ΠΌΠΈ Π³ΠΎΡΠΎΠ²ΠΈΠΉ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈΡΡ, Π²ΡΠΈΡΠΈΡΡ ΡΠ° Π²ΡΠΈΡΠΈ.
Π ΡΠ΅ β ΠΌΠΈ Π»Π°ΠΌΠ°ΡΠΌΠΎ ΡΡΠ΅ΡΠ΅ΠΎΡΠΈΠΏΠΈ, ΡΠΎ ΡΠΈΡΠ΅ΠΉΠ» β ΡΠΎ Π»ΠΈΡΠ΅ ΠΏΡΠΎ ΠΏΠΎΠΌΡΠ΄ΠΎΡΡΠΈΠΊΠΈ. ΠΠΎΠ²ΡΡ, ΡΠ΅Ρ Π½ΡΡΠ½Π° ΡΠ°ΡΡΠΈΠ½Π° Π½Π°ΡΠΈΡ ΠΏΡΠΎΠ΅ΠΊΡΡΠ² Π΄Π°Ρ ΡΡΠ»Π΅ ΠΏΠΎΠ»Π΅ Π΄Π»Ρ ΠΊΡΠ΅Π°ΡΠΈΠ²Ρ ΡΠ° ΠΏΡΠΎΠΊΠ°ΡΠΊΠΈ Π΄ΡΠΌΠ°Π»ΠΊΠΈ.
Π©ΠΎ Ρ Π½Π°Ρ Π·Π°ΡΠ°Π· Π² ΡΠΎΠ±ΠΎΡΡ:
β ΠΏΡΠΎΠΊΠ°ΡΡΡΠΌΠΎ Π½Π°ΡΠ²Π½Ρ Π΄ΠΎΡΡΠ°Π²ΠΊΡ ΡΠΈΡΠΎΠΊΠΎΠ³ΠΎ Π°ΡΠΎΡΡΠΈΠΌΠ΅Π½ΡΡ Π· ΠΌΠ°Π³Π°Π·ΠΈΠ½ΡΠ² Π‘ΡΠ»ΡΠΏΠΎ;
β ΡΠΎΠ·ΡΠΎΠ±Π»ΡΡΠΌΠΎ Π½Π°Π΄ΡΠ²ΠΈΠ΄ΠΊΡ Π΄ΠΎΡΡΠ°Π²ΠΊΡ ΠΏΡΠΎΠ΄ΡΠΊΡΡΠ² ΡΠ° ΡΡΡΠ°Π² ΠΏΡΠ΄ Π½ΠΎΠ²ΠΈΠΌ Π±ΡΠ΅Π½Π΄ΠΎΠΌ LOKO.
Π Π² ΠΏΠ»Π°Π½Π°Ρ ΡΠ΅ Π΄ΡΡΡΠΆΠ΅ Π±Π°Π³Π°ΡΠΎ ΡΠΎΠ±ΠΎΡΠΈ Π· Π°ΠΌΠ±ΡΡΠ½ΠΈΠΌΠΈ Π·Π°Π΄Π°ΡΠ°ΠΌΠΈ ΡΠ° Π²ΠΈΠΊΠ»ΠΈΠΊΠ°ΠΌΠΈ.
ΠΠ° ΡΠΊΠΈΡ ΡΡΠ½Π½ΠΎΡΡΡΡ Π±ΡΠ΄ΡΡΠΌΠΎ ΠΏΡΠΎΠ΅ΠΊΡΠΈ?
β Π£ΠΊΡΠ°ΡΠ½ΡΡΠΊΠΈΠΉ ΠΏΡΠΎΠ΄ΡΠΊΡ Π΄Π»Ρ ΡΠΊΡΠ°ΡΠ½ΡΡΠ². Π‘Π²ΠΎΡ Π΄Π»Ρ ΡΠ²ΠΎΡΡ . ΠΠ°ΡΡ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈ Π²Π°ΠΆΠ»ΠΈΠ²Ρ ΡΠ° ΠΊΠΎΡΠΈΡΠ½Ρ ΠΠΎΡΡΡΠΌ, ΡΠ²ΠΎΡΠΉ ΡΡΠΌβΡ ΡΠ° ΡΠ²ΠΎΡΠΌ Π΄ΡΡΠ·ΡΠΌ. Π ΡΠ΅ Π±ΡΠ΄Π΅ Π°ΠΊΡΡΠ°Π»ΡΠ½ΠΎ Ρ ΡΡΠΎΠ³ΠΎΠ΄Π½Ρ, Ρ Π·Π°Π²ΡΡΠ°, Ρ ΠΏΡΡΠ»Ρ ΠΠ΅ΡΠ΅ΠΌΠΎΠ³ΠΈ;
β Agile mindset Π½Π΅ Π½Π° ΡΠ»ΠΎΠ²Ρ, Π° Π½Π° Π΄ΡΠ»Ρ. Π ΡΠΎΠ»ΠΊΠΎΠΌ, ΡΡΠ²ΡΠ΄ΠΎΠΌΠ»Π΅Π½ΠΎ ΡΠ° Π²ΠΈΡ ΠΎΠ΄ΡΡΠΈ Π· Π½Π°ΡΠΎΠ³ΠΎ ΠΊΠΎΠ½ΡΠ΅ΠΊΡΡΡ. Π’ΠΎΠΆ, ΡΠΊΡΠΎ ΡΠΈ Π°Π΄Π΅ΠΏΡ Π°Π΄ΠΆΠ°ΠΉΠ»Ρ β ΡΠΎΠ±Ρ Π· Π½Π°ΠΌΠΈ ΡΠΏΠΎΠ΄ΠΎΠ±Π°ΡΡΡΡΡ;
β ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π²ΠΏΠ»ΠΈΠ²Π°ΡΠΈ Π½Π° ΠΏΡΠΎΠ΄ΡΠΊΡ. ΠΠΈ Π½Π°Π±ΠΈΡΠ°ΡΠΌΠΎ Π·ΡΡΠΎΡΠΎΠΊ ΡΠ° Π΄Π°ΡΠΌΠΎ ΡΠΌ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΡΡΡΡΠΈ ΡΠ° ΡΠΈΠΌ ΡΠ°ΠΌΠΈΠΌ Π·Π°ΠΏΠ°Π»ΡΠ²Π°ΡΠΈ Π½Π°ΡΡ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈ. ΠΠ΄ΠΎΡΠΎΠ²ΠΈΠΉ Π³Π»ΡΠ·Π΄ Π΄Π»Ρ Π½Π°Ρ ΡΡΠ½Π½ΡΡΠΈΠΉ, Π½ΡΠΆ Β«ΡΠ°ΠΊ ΡΡΡΠΎΡΠΈΡΠ½ΠΎ ΡΠΊΠ»Π°Π»ΠΎΡΡΒ».
Π―ΠΊ ΠΌΠΈ Π±Π°ΡΠΈΠΌΠΎ Π½Π°ΡΠΎΠ³ΠΎ dream ΠΊΠ°Π½Π΄ΠΈΠ΄Π°ΡΠ° ΡΠΈ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°ΡΠΊΡ?
β Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π½Π° Π°Π½Π°Π»ΠΎΠ³ΡΡΠ½ΡΠΉ ΠΏΠΎΡΠ°Π΄Ρ Π²ΡΠ΄ 3-Ρ ΡΠΎΠΊΡΠ²;
β ΠΏΡΠΎΡΡΠ½ΡΡΠ΅ Π²ΠΎΠ»ΠΎΠ΄ΡΠ½Π½Ρ BI-ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΠΌΠΈ (Power BI / Tableau);
β Π²ΡΠ΄ΠΌΡΠ½Π½Π΅ Π·Π½Π°Π½Π½Ρ SQL (Π²ΡΠΊΠΎΠ½Π½Ρ ΡΡΠ½ΠΊΡΡΡ, Π°Π½Π°Π»ΡΡΠΈΡΠ½Ρ ΡΡΠ½ΠΊΡΡΡ, cte);β ΠΎΡΠ²ΡΡΠ° Π² Π³Π°Π»ΡΠ·Ρ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ, Π΅ΠΊΠΎΠ½ΠΎΠΌΡΠΊΠΈ, ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ, ΠΊΠΎΠΌΠΏβΡΡΠ΅ΡΠ½ΠΈΡ Π½Π°ΡΠΊ, ΡΡΠ½Π°Π½ΡΡΠ² Π°Π±ΠΎ ΡΠΏΠΎΡΡΠ΄Π½Π΅Π½ΠΈΡ Π½Π°ΠΏΡΡΠΌΡΠ²;
β Π°Π½Π°Π»ΡΡΠΈΡΠ½Ρ Π·Π½Π°Π½Π½Ρ: Π³Π»ΠΈΠ±ΠΎΠΊΡ Π·Π½Π°Π½Π½Ρ ΠΉΠΌΠΎΠ²ΡΡΠ½ΠΎΡΡΡ, ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ, ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ Π΄Π°Π½ΠΈΡ , Π²ΡΠ·ΡΠ°Π»ΡΠ·Π°ΡΡΡ Π΄Π°Π½ΠΈΡ ΡΠ° Π΄ΠΈΠ·Π°ΠΉΠ½Ρ Π΄Π°ΡΠ±ΠΎΡΠ΄ΡΠ²;
β Π±Π°ΠΆΠ°Π½Π½Ρ Π²ΡΠΈΡΠΈΡΡ, Π΄ΠΎΠΏΠΈΡΠ»ΠΈΠ²ΡΡΡΡ, Π²ΡΠ΄ΠΌΡΠ½Π½Ρ ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΠΈΠ²Π½Ρ ΡΠ° Π½Π°Π²ΠΈΡΠΊΠΈ ΠΊΠΎΠΌΠ°Π½Π΄Π½ΠΎΡ ΡΠΎΠ±ΠΎΡΠΈ.
ΠΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ:
β ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΊΠΎΠ½ΡΠ΅ΠΏΡΡΠΉ Data Warehousing Ρ ΡΠ΅Ρ Π½ΡΠΊ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ Π΄Π°Π½ΠΈΡ ;
β Π·Π½Π°Π½Π½Ρ Airflow Π°Π±ΠΎ ΠΏΠΎΠ΄ΡΠ±Π½ΠΈΡ ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΡΠ² Π΄Π»Ρ ΠΎΡΠΊΠ΅ΡΡΡΠ°ΡΡΡ ΡΠΎΠ±ΠΎΡΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠ² Π· Π΄Π°Π½ΠΈΠΌΠΈ;
β Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· dbt (data build tool) Π΄Π»Ρ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ Ρ ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΡΡ Π΄Π°Π½ΠΈΡ ;β Π½Π°Π²ΠΈΡΠΊΠΈ ΡΠΎΠ±ΠΎΡΠΈ Π· Python (numpy, pandas, sklearn) Π΄Π»Ρ ΠΏΡΠΎΡΡΠ½ΡΡΠΎΡ Π°Π½Π°Π»ΡΡΠΈΠΊΠΈ ΡΠΈ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΡΡ;
β Π±Π°Π·ΠΎΠ²Ρ Π·Π½Π°Π½Π½Ρ ΡΠ΅Ρ Π½ΡΠΊ ΠΌΠ°ΡΠΈΠ½Π½ΠΎΠ³ΠΎ Π½Π°Π²ΡΠ°Π½Π½Ρ ML ΡΠ° ΡΡ Π½ΡΠΎΠ³ΠΎ Π·Π°ΡΡΠΎΡΡΠ²Π°Π½Π½Ρ Π² Π°Π½Π°Π»ΡΡΠΈΡΡ.
Π©ΠΎ ΡΠΈ Π±ΡΠ΄Π΅Ρ ΡΠΎΠ±ΠΈΡΠΈ?
β ΡΠΏΡΠ²ΠΏΡΠ°ΡΡ Π² ΠΌΡΠΆΡΡΠ½ΠΊΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ ΠΊΠΎΠΌΠ°Π½Π΄Π°Ρ : Π·Π±ΠΈΡΠ°ΡΠΈ Π²ΠΈΠΌΠΎΠ³ΠΈ, ΠΏΠ΅ΡΠ΅ΡΠ²ΠΎΡΡΠ²Π°ΡΠΈ ΡΡ Π½Π° ΠΌΠ°ΡΡΡΠ°Π±ΠΎΠ²Π°Π½Ρ ΡΠ° Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½Ρ data-ΠΏΡΠΎΠ΄ΡΠΊΡΠΈ ΡΠ° Π±ΡΠ°ΡΠΈ ΡΡΠ°ΡΡΡ Ρ ΠΊΠ»ΡΡΠΎΠ²ΠΈΡ ΠΊΠΎΠΌΠ΅ΡΡΡΠΉΠ½ΠΈΡ ΡΠ½ΡΡΡΠ°ΡΠΈΠ²Π°Ρ , ΡΠ°ΠΊΠΈΡ ΡΠΊ - Π°Π½Π°Π»ΡΠ· Π°ΡΠΎΡΡΠΈΠΌΠ΅Π½ΡΡ, Π΄ΠΈΠ½Π°ΠΌΡΡΠ½Π΅ ΡΡΠ½ΠΎΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ, Π°Π½Π°Π»ΡΡΠΈΠΊΠ° ΠΏΠΎΡΡΠ°ΡΠ°Π»ΡΠ½ΠΈΠΊΡΠ² Ρ ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ ΠΊΠΎΠ½ΡΠ΅Π½ΡΠΎΠΌ;
β Π°Π½Π°Π»ΡΠ· Π΄Π°Π½ΠΈΡ : Π²ΠΈΠΊΠΎΠ½ΡΠ²Π°ΡΠΈ Π³Π»ΠΈΠ±ΠΎΠΊΠΈΠΉ Π°Π½Π°Π»ΡΠ· Π΄Π°Π½ΠΈΡ Π΄Π»Ρ ΠΏΡΠΎΠ΄ΡΠΊΡΡΠ², ΡΠ΅ΡΠ²ΡΡΡΠ² Ρ ΡΡΠ½ΠΊΡΡΠΉ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠ΄ΡΠΎΠ·Π΄ΡΠ»ΡΠ², ΠΎΡΡΠ½ΡΠ²Π°ΡΠΈ ΡΠ° ΠΏΡΠΎΠ³Π½ΠΎΠ·ΡΠ²Π°ΡΠΈ ΡΡ Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΡΡΡΡ;
β ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ° Π΄Π°ΡΠ±ΠΎΡΠ΄ΡΠ²: ΡΡΠ²ΠΎΡΡΠ²Π°ΡΠΈ ΠΏΡΠΎΡΠ΅ΡΡΠΉΠ½Ρ, ΡΠ½ΡΡΡΡΠΈΠ²Π½ΠΎ Π·ΡΠΎΠ·ΡΠΌΡΠ»Ρ Π΄Π°ΡΠ±ΠΎΡΠ΄ΠΈ Π·Π° Π΄ΠΎΠΏΠΎΠΌΠΎΠ³ΠΎΡ Power BI Π΄Π»Ρ ΠΌΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³Ρ ΠΊΠ»ΡΡΠΎΠ²ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π½ΠΈΠΊΡΠ², ΠΎΡΡΠ½ΠΊΠΈ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΡΠΎΠ΅ΠΊΡΡΠ² Ρ Π½Π°Π΄Π°Π½Π½Ρ ΡΠ½ΡΠ°ΠΉΡΡΠ² Π΄Π»Ρ ΠΎΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡ ΠΏΡΠΎΠ΄ΡΠΊΡΡΠ² Ρ Π±ΡΠ·Π½Π΅Ρ-Π½Π°ΠΏΡΡΠΌΡΠ²;
β ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π· Π΄Π°Π½ΠΈΠΌΠΈ, Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΡΡΠΈ SQL ΡΠ° dbt Π΄Π»Ρ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ, ΡΡΠ°Π½ΡΡΠΎΡΠΌΠ°ΡΡΡ ΡΠ° ΠΏΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠΈ Π΄Π°Π½ΠΈΡ Ρ ΡΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡΡ Π½Π°ΡΠΎΠ³ΠΎ data warehouse.
ΠΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:β ΡΠΎΠ±ΠΎΡΡ Π½Π°Π΄ ΡΠ»Π°Π³ΠΌΠ°Π½ΡΡΠΊΠΈΠΌ ΠΏΡΠΎΠ΅ΠΊΡΠΎΠΌ Π· Π²Π΅Π»ΠΈΠΊΠΎΡ ΠΊΡΠ»ΡΠΊΡΡΡΡ ΡΠ·Π΅ΡΡΠ²;
β ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π²ΡΠ΄Π΄Π°Π»Π΅Π½ΠΎΡ ΡΠΎΠ±ΠΎΡΠΈ Π°Π±ΠΎ ΠΎΡΡΡ Π· Π³Π΅Π½Π΅ΡΠ°ΡΠΎΡΠΎΠΌ ΡΠ° ΡΡΠ°ΡΠ»ΡΠ½ΠΊΠΎΠΌ (ΠΎΡΡΡ Π² ΠΠ¦ SilverBreeze Π½Π° ΠΠ΅ΡΠ΅Π·Π½ΡΠΊΠ°Ρ );
β Π³Π½ΡΡΠΊΠΈΠΉ Π³ΡΠ°ΡΡΠΊ;
β ΠΌΠ΅Π΄ΠΈΡΠ½Π΅ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ;
β ΡΠΈΠ·ΠΈΠΊΠΎΠ²Π΅ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ ΠΆΠΈΡΡΡ;
β ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° Π€ΠΠ/ΠΠΠ- ΠΊΠΎΠ½ΡΡΠ°ΠΊΡ;
β Π·Π½ΠΈΠΆΠΊΠΈ Ρ ΠΌΠ°Π³Π°Π·ΠΈΠ½Π°Ρ ΡΠ° ΡΠ΅ΡΡΠΎΡΠ°Π½Π°Ρ Fozzy Group;
β ΠΏΡΠΈΡ ΠΎΠ»ΠΎΠ³ΡΡΠ½Π° ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ°;
β ΡΡΡΠ±ΠΎΡΠ»ΠΈΠ²Ρ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Ρ ΠΊΡΠ»ΡΡΡΡΡ, ΡΠΊΡ ΠΌΠΈ ΡΠ°Π·ΠΎΠΌ Π· ΡΠΎΠ±ΠΎΡ Π±ΡΠ΄Π΅ΠΌΠΎ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈ;
β ΠΊΠΎΠΌΠ°Π½Π΄Ρ, Π· ΡΠΊΠΎΡ ΡΠΈ Π·ΠΌΠΎΠΆΠ΅Ρ ΡΠ΅Π°Π»ΡΠ·ΡΠ²Π°ΡΠΈ ΡΠ²ΠΎΡ ΡΠ΄Π΅Ρ, Π΅ΠΊΡΠΏΠ΅ΡΠΈΠΌΠ΅Π½ΡΡΠ²Π°ΡΠΈ Ρ Π²ΡΠ΄ΡΡΠ²Π°ΡΠΈ ΡΠ΅Π±Π΅ Π² ΠΊΠΎΠ»Ρ Π΄ΡΡΠ·ΡΠ²;
β Ρ ΡΡΠ»Π° ΠΊΡΠΏΠ° ΡΡΡΠ±ΠΎΡΠΈΠ½ΠΎΠΊ (ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ (Π² Π£ΠΊΡΠ°ΡΠ½Ρ), Π·Π½ΠΈΠΆΠΊΠΈ Π² Π½Π°ΡΠΈΡ Π±ΡΠ·Π½Π΅ΡΠ°Ρ ΡΠ° Ρ ΠΏΠ°ΡΡΠ½Π΅ΡΡΠ²).
ΠΡΠΎΡΠ΅, Π½Π°ΡΠ°Π·Ρ Π² ΡΡΠ»ΡΡ Π±Π΅Π·ΠΏΠ΅ΠΊΠΈ, ΠΌΠΈ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄ΡΡΠΌΠΎ ΡΠΊΠΎΡΠΎΡΡΠ²Π°ΡΠΈ ΠΏΠΎΡΠ·Π΄ΠΊΠΈ Π² ΠΎΡΡΡ.
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Β· 83 views Β· 6 applications Β· 17d
Data Analyst
Hybrid Remote Β· Ukraine (Lviv) Β· Product Β· 1 year of experience Β· A1 - BeginnerΠ£ Π₯ΠΎΠ»Π΄ΠΈΠ½Π³Ρ Π΅ΠΌΠΎΡΡΠΉ "!FEST" ΠΌΠΈ Π΄ΠΎΡΡΠΈΠΌΡΡΠΌΠΎΡΡ ΠΏΡΠΈΠ½ΡΠΈΠΏΡ ΡΠΎΠ±ΠΈΡΠΈ ΡΠ΅Π±Π΅, ΠΌΡΡΡΠΎ, ΠΊΡΠ°ΡΠ½Ρ ΡΠ° ΡΠ²ΡΡ ΠΊΡΠ°ΡΠΈΠΌΠΈ, ΡΠΎΠΆ Π΄Π°ΡΠΌΠΎ Π½Π°ΡΠΈΠΌ ΠΏΡΠ°ΡΡΠ²Π½ΠΈΠΊΠ°ΠΌ Π·ΠΌΠΎΠ³Ρ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎ ΡΠ΅Π°Π»ΡΠ·ΡΠ²Π°ΡΠΈ ΡΠ΅Π±Π΅ ΡΠΊ Π² Π½Π°Π²ΠΈΠΊΠ°Ρ , ΡΠ°ΠΊ Ρ Π² ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡΡ Π½Π°Π²ΡΠ°ΡΠΈΡΡ, Π²Π΄ΠΎΡΠΊΠΎΠ½Π°Π»ΡΠ²Π°ΡΠΈΡΡ ΡΠ° Π΄ΠΎΡΡΠ³Π°ΡΠΈ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡΠ². ΠΡΠΎ...Π£ Π₯ΠΎΠ»Π΄ΠΈΠ½Π³Ρ Π΅ΠΌΠΎΡΡΠΉ "!FEST" ΠΌΠΈ Π΄ΠΎΡΡΠΈΠΌΡΡΠΌΠΎΡΡ ΠΏΡΠΈΠ½ΡΠΈΠΏΡ ΡΠΎΠ±ΠΈΡΠΈ ΡΠ΅Π±Π΅, ΠΌΡΡΡΠΎ, ΠΊΡΠ°ΡΠ½Ρ ΡΠ° ΡΠ²ΡΡ ΠΊΡΠ°ΡΠΈΠΌΠΈ, ΡΠΎΠΆ Π΄Π°ΡΠΌΠΎ Π½Π°ΡΠΈΠΌ ΠΏΡΠ°ΡΡΠ²Π½ΠΈΠΊΠ°ΠΌ Π·ΠΌΠΎΠ³Ρ ΠΌΠ°ΠΊΡΠΈΠΌΠ°Π»ΡΠ½ΠΎ ΡΠ΅Π°Π»ΡΠ·ΡΠ²Π°ΡΠΈ ΡΠ΅Π±Π΅ ΡΠΊ Π² Π½Π°Π²ΠΈΠΊΠ°Ρ , ΡΠ°ΠΊ Ρ Π² ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡΡ Π½Π°Π²ΡΠ°ΡΠΈΡΡ, Π²Π΄ΠΎΡΠΊΠΎΠ½Π°Π»ΡΠ²Π°ΡΠΈΡΡ ΡΠ° Π΄ΠΎΡΡΠ³Π°ΡΠΈ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡΠ².
ΠΡΠΎ ΠΊΠΎΠΌΠ°Π½Π΄Ρ:
Π’ΠΈ ΡΡΠ°Π½Π΅Ρ ΡΠ°ΡΡΠΈΠ½ΠΎΡ Π΄ΠΈΠ½Π°ΠΌΡΡΠ½ΠΎΡ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ Π°Π½Π°Π»ΡΡΠΈΠΊΡΠ² Π΄Π°Π½ΠΈΡ , ΡΠ½ΠΆΠ΅Π½Π΅ΡΡΠ² ΡΠ° Π½Π°ΡΠΊΠΎΠ²ΡΡΠ², ΡΠΊΡ Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΡΡΡ Π΄Π°Π½Ρ, ΡΠΎΠ± Π΄ΠΎΠΏΠΎΠΌΠΎΠ³ΡΠΈ Π½Π°ΡΡΠΉ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ ΠΏΡΠΈΠΉΠΌΠ°ΡΠΈ ΠΊΡΠ°ΡΡ ΡΡΡΠ΅Π½Π½Ρ.
ΠΡΠ΄Π΅Ρ ΡΠΏΡΠ²ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π·:
- 2-ΠΎΠΌΠ° Π΄Π°ΡΠ°-Π°Π½Π°Π»ΡΡΠΈΠΊΠ°ΠΌΠΈ;
- Π΄Π°ΡΠ°-ΡΠ½ΠΆΠ΅Π½Π΅ΡΠΎΠΌ;
- 2-ΠΎΠΌΠ° Π΄Π°ΡΠ°-ΡΠ°ΡΠ½ΡΠΈΡΡΠ°ΠΌΠΈ;
- ΡΠ½ΠΆΠ΅Π½Π΅ΡΠΎΠΌ Π· Π³ΡΠ°ΡΡΠ² Π·Π½Π°Π½Ρ;
- ΡΠΎΡΡΠΎΠ»ΠΎΠ³ΠΎΠΌ;
- Π±ΡΠ·Π½Π΅Ρ-Π°Π½Π°Π»ΡΡΠΈΠΊΠΎΠΌ.
Π©ΠΎ Π±ΡΠ΄Π΅Ρ ΡΠΎΠ±ΠΈΡΠΈ?
- ΠΠ²ΡΠΎΠΌΠ°ΡΠΈΠ·ΡΠ²Π°ΡΠΈ Π°Π½Π°Π»ΡΡΠΈΡΠ½Ρ Π·Π°Π²Π΄Π°Π½Π½Ρ, Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΡΡΠΈ Python, SQL ΡΠ° ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠΈ Π²ΡΠ·ΡΠ°Π»ΡΠ·Π°ΡΡΡ (Power BI, Looker).
- Π ΠΎΠ·ΡΠΎΠ±Π»ΡΡΠΈ ΡΠ° ΠΎΠ±ΡΠ»ΡΠ³ΠΎΠ²ΡΠ²Π°ΡΠΈ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΠΉΠ½Ρ ΠΏΠ°Π½Π΅Π»Ρ ΠΉ Π·Π²ΡΡΠΈ Π΄Π»Ρ ΠΊΠ»ΡΡΠΎΠ²ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π½ΠΈΠΊΡΠ² Π±ΡΠ·Π½Π΅ΡΡ.
- Π‘ΠΏΡΠ²ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π· ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ Π΄Π»Ρ Π²ΠΈΡΡΡΠ΅Π½Π½Ρ ΡΠΊΠ»Π°Π΄Π½ΠΈΡ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΡ ΠΏΡΠΎΠ±Π»Π΅ΠΌ.
- ΠΠΈΠΊΠΎΠ½ΡΠ²Π°ΡΠΈ ad-hoc Π·Π°ΠΏΠΈΡΠΈ Π²ΡΠ΄ Π·Π°ΡΡΠΊΠ°Π²Π»Π΅Π½ΠΈΡ ΡΡΠΎΡΡΠ½.
- ΠΠ°Π»Π΅ΠΆΠ½ΠΎ Π²ΡΠ΄ ΡΡΠ²Π½Ρ Π΄ΠΎΡΠ²ΡΠ΄Ρ ΡΠ° Π±Π°ΠΆΠ°Π½Π½Ρ, Π±ΡΠ°ΡΠΈ ΡΡΠ°ΡΡΡ Ρ ΠΏΡΠΎΡΠΊΡΠ°Ρ Π· Π½Π°ΡΠΊΠΈ ΠΏΡΠΎ Π΄Π°Π½Ρ.
Π©ΠΎ ΠΎΡΡΠΊΡΡΠΌΠΎ Π²ΡΠ΄ ΡΠ΅Π±Π΅?
- ΠΠΏΠ΅Π²Π½Π΅Π½Π΅ Π²ΠΎΠ»ΠΎΠ΄ΡΠ½Π½Ρ Π±Π°Π·Π°ΠΌΠΈ Π΄Π°Π½ΠΈΡ (BigQuery, MySQL, SQL Server);
- ΠΠ½Π°Π½Π½Ρ Apache Airflow (Π±ΡΠ΄Π΅ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΎΡ);
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠ°ΠΌΠΈ Google Cloud Platform (Π±ΡΠ΄Π΅ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΎΡ);
- ΠΠΌΡΠ½Π½Ρ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π· Power BI Π°Π±ΠΎ Looker (Π±ΡΠ΄Π΅ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΎΡ);
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΏΡΠΎΠ΅ΠΊΡΠ°ΠΌΠΈ Π· Π½Π°ΡΠΊΠΈ ΠΏΡΠΎ Π΄Π°Π½Ρ (Π±ΡΠ΄Π΅ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΎΡ);
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Π°Π½Π°Π»ΡΡΠΈΠΊΠΎΡ Π΄Π°Π½ΠΈΡ Π·Π° Π΄ΠΎΠΏΠΎΠΌΠΎΠ³ΠΎΡ Python;
- ΠΡΠ΄ΠΌΡΠ½Π½Ρ Π°Π½Π°Π»ΡΡΠΈΡΠ½Ρ Π½Π°Π²ΠΈΡΠΊΠΈ ΡΠ° Π½Π°Π²ΠΈΡΠΊΠΈ Π²ΠΈΡΡΡΠ΅Π½Π½Ρ ΠΏΡΠΎΠ±Π»Π΅ΠΌ;
- Π‘ΠΈΠ»ΡΠ½Ρ ΠΊΠΎΠΌΡΠ½ΡΠΊΠ°ΡΠΈΠ²Π½Ρ ΡΠ° ΠΏΡΠ΅Π·Π΅Π½ΡΠ°ΡΡΠΉΠ½Ρ Π½Π°Π²ΠΈΡΠΊΠΈ;
- ΠΠ΄Π°ΡΠ½ΡΡΡΡ Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ ΡΠΊ ΡΠ°ΠΌΠΎΡΡΡΠΉΠ½ΠΎ, ΡΠ°ΠΊ Ρ Π² ΠΊΠΎΠΌΠ°Π½Π΄Ρ.
Π©ΠΎ ΠΌΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ?
- ΠΠΎΠ½ΠΊΡΡΠ΅Π½ΡΠ½Ρ Π·Π°ΡΠΎΠ±ΡΡΠ½Ρ ΠΎΠΏΠ»Π°ΡΡ;
- ΠΠ½ΠΈΠΆΠΊΠΈ Π² ΠΌΠ΅ΡΠ΅ΠΆΡ Π΄Π»Ρ ΠΊΠΎΠΆΠ½ΠΎΠ³ΠΎ ΠΏΡΠ°ΡΡΠ²Π½ΠΈΠΊΠ° ;
- ΠΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π½Π°Π΄ ΡΡΠΊΠ°Π²ΠΈΠΌΠΈ ΡΠ° ΡΠΊΠ»Π°Π΄Π½ΠΈΠΌΠΈ ΠΏΡΠΎΠ΅ΠΊΡΠ°ΠΌΠΈ, ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° ΠΊΠΎΠ»Π΅Π³ Π½Π° Π²ΡΡΡ Π΅ΡΠ°ΠΏΠ°Ρ ΡΠΎΠ±ΠΎΡΠΈ;
- ΠΠΎΠΌΡΠΎΡΡΠ½ΠΈΠΉ ΠΎΡΡΡ, Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½ΠΈΠΉ ΡΠΊΡΠΈΡΡΡΠΌ ΡΠ° Π²ΡΡΠΌ Π½Π΅ΠΎΠ±Ρ ΡΠ΄Π½ΠΈΠΌ Π΄Π»Ρ Π°Π²ΡΠΎΠ½ΠΎΠΌΠ½ΠΎΡ ΡΠΎΠ±ΠΎΡΠΈ ΠΏΡΠ΄ ΡΠ°Ρ Π²ΡΠ΄ΠΊΠ»ΡΡΠ΅Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΈΠΊΠΈ ΡΠ° Π±Π»Π΅ΠΊΠ°ΡΡΡΠ²;
- Π¦ΡΠΊΠ°Π²Π° ΡΠΎΠ±ΠΎΡΠ° Π² Π΄ΡΡΠΆΠ½ΡΠΉ, ΡΠ΄Π΅ΠΉΠ½ΡΠΉ ΡΠ° Π½Π°ΡΡ Π½Π΅Π½Π½ΡΠΉ ΠΊΠΎΠΌΠ°Π½Π΄Ρ.
Π―ΠΊΡΠΎ ΠΌΠ°ΡΡ Π±Π°ΠΆΠ°Π½Π½Ρ ΡΠΎΠ·Π²ΠΈΠ²Π°ΡΠΈΡΡ ΡΠ° ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π² ΠΊΠΎΠΌΠ°Π½Π΄Ρ ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ², ΡΠΎΠ΄Ρ ΡΡ Π²Π°ΠΊΠ°Π½ΡΡΡ ΡΠ°ΠΌΠ΅ Π΄Π»Ρ ΡΠ΅Π±Π΅. ΠΡΠΈΡΠ΄Π½ΡΠΉΡΡ Π΄ΠΎ Π½Π°Ρ!
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Β· 52 views Β· 1 application Β· 6d
System Analyst to $3500
Hybrid Remote Β· Ukraine Β· Product Β· 3 years of experienceΠ ΠΊΠΎΠΌΠ°Π½Π΄Ρ Π΄Π»Ρ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ DWH ΡΠ° ΠΏΠΎΠ²βΡΠ·Π°Π½ΠΈΡ Π· Π½ΠΈΠΌ ΡΠ΅ΡΠ²ΡΡΡΠ² Π³ΡΡΠΏΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΠΉ ΠΠΏΡΡΠ΅Π½ΡΡ ΠΏΠΎΡΡΡΠ±Π΅Π½ Π‘ΠΈΡΡΠ΅ΠΌΠ½ΠΈΠΉ Π°Π½Π°Π»ΡΡΠΈΠΊ ΠΡΠΎ ΠΏΡΠΎΠ΅ΠΊΡ ΠΡΠΎΠ΅ΠΊΡ Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΡΡ Π³ΡΡΠΏΡ ΠΊΠΎΠΌΠΏΠ°Π½ΡΠΉ ΠΠΏΡΡΠ΅Π½ΡΡ (ΡΠΎΡΠ³ΠΎΠ²Π΅Π»ΡΠ½Π° ΠΌΠ΅ΡΠ΅ΠΆΠ° ΠΠΏΡΡΠ΅Π½ΡΡΠ, ΠΠΏΡΡΠ΅Π½ΡΡΠΠ³ΡΠΎ, Epicentr Ceramic Corporation, Epicentrk.ua,...Π ΠΊΠΎΠΌΠ°Π½Π΄Ρ Π΄Π»Ρ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ DWH ΡΠ° ΠΏΠΎΠ²βΡΠ·Π°Π½ΠΈΡ Π· Π½ΠΈΠΌ ΡΠ΅ΡΠ²ΡΡΡΠ² Π³ΡΡΠΏΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΠΉ ΠΠΏΡΡΠ΅Π½ΡΡ ΠΏΠΎΡΡΡΠ±Π΅Π½ Π‘ΠΈΡΡΠ΅ΠΌΠ½ΠΈΠΉ Π°Π½Π°Π»ΡΡΠΈΠΊ
ΠΡΠΎ ΠΏΡΠΎΠ΅ΠΊΡ
ΠΡΠΎΠ΅ΠΊΡ Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΡΡ Π³ΡΡΠΏΡ ΠΊΠΎΠΌΠΏΠ°Π½ΡΠΉ ΠΠΏΡΡΠ΅Π½ΡΡ (ΡΠΎΡΠ³ΠΎΠ²Π΅Π»ΡΠ½Π° ΠΌΠ΅ΡΠ΅ΠΆΠ° ΠΠΏΡΡΠ΅Π½ΡΡΠ, ΠΠΏΡΡΠ΅Π½ΡΡΠΠ³ΡΠΎ, Epicentr Ceramic Corporation, Epicentrk.ua, ΠΠ°ΡΠΊΠ΅ΡΠΏΠ»Π΅ΠΉΡ ΠΠΏΡΡΠ΅Π½ΡΡ) ΡΠ²ΠΈΠ΄ΠΊΠΎΡ, ΡΠΎΡΠ½ΠΎΡ ΡΠ° Π·ΡΡΡΠ½ΠΎΡ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΎΡ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡΡ. Π Π·Π°Π΄Π°ΡΡ ΠΏΡΠΎΠ΅ΠΊΡΡ Π²Ρ ΠΎΠ΄ΠΈΡΡ:
Β· ΠΠΎΠ±ΡΠ΄ΠΎΠ²Π° DWH, ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ° ETL-ΠΏΡΠΎΡΠ΅ΡΡΠ², API
Β· Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΡΠ° ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΡ ΠΊΡΠ±ΡΠ²
Β· Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΡΠ° ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° ΡΠ΅ΡΠ²ΡΡΡ MDM
Β· Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° Π·Π²ΡΡΠ½ΠΎΡΡΡ Π· Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½ΡΠΌ Power BI
Β· Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° Ρ ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠ° ΡΠΈΡΡΠ΅ΠΌΠΈ Π·Π²ΡΡΠ½ΠΎΡΡΡ Π΄Π»Ρ Π·ΠΎΠ²Π½ΡΡΠ½ΡΡ ΠΊΠΎΠ½ΡΡΠ°Π³Π΅Π½ΡΡΠ²
ΠΠ΅ΠΎΠ±Ρ ΡΠ΄Π½Ρ Π½Π°Π²ΠΈΡΠΊΠΈ
Β· ΠΠ½Π°Π½Π½Ρ ΡΠ° Π½Π°Π²ΠΈΠΊΠΈ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ JIRA+Confluence
Β· ΠΠΌΡΠ½Π½Ρ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ BPMN, UML ΡΠ° ERD Π΄ΡΠ°Π³ΡΠ°ΠΌ
Β· Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ Scrum, Agile
Β· Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΡΠ° Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· ΠΠ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΡΠ²Π½Ρ, ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΏΡΠΈΠ½ΡΠΈΠΏΡΠ² ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ ΡΡ ΠΎΠ²ΠΈΡΠ° Π΄Π°Π½ΠΈΡ ΡΠ° ETL-ΠΏΡΠΎΡΠ΅ΡΡΠ²
Β· ΠΠ½Π°Π½Π½Ρ T-SQL
Β· Π ΡΠ²Π΅Π½Ρ Π²ΠΎΠ»ΠΎΠ΄ΡΠ½Π½Ρ Π°Π½Π³Π»ΡΠΉΡΡΠΊΠΎΡ ΠΌΠΎΠ²ΠΎΡ: Π§ΠΈΡΠ°Π½Π½Ρ ΡΠ° ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΡΠ΅Ρ Π½ΡΡΠ½ΠΎΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡ Π°Π±ΠΎ Π²ΠΈΡΠ΅.
ΠΡΠ΄Π΅ ΠΏΠ»ΡΡΠΎΠΌ
Β· ΡΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΡ OLAP
Β· Π΄ΠΎΡΠ²ΡΠ΄ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ ΠΎΠ±ΠΌΡΠ½ΡΠ² Π· Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½ΡΠΌ RabbitMQ, API
Β· Π΄ΠΎΡΠ²ΡΠ΄ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ Π°Π±ΠΎ ΡΠΎΠ±ΠΎΡΠΈ Π· MDM-ΡΠΈΡΡΠ΅ΠΌΠ°ΠΌΠΈ
Β· ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ, ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΠΈ Π°Π±ΠΎ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ BI ΡΠΈΡΡΠ΅ΠΌ
Β· ΠΠ½Π°Π½Π½Ρ DAX
ΠΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ
Π£ΡΠ°ΡΡΡ Π² Π΄ΠΎΠ²Π³ΠΎΡΡΠΈΠ²Π°Π»ΠΎΠΌΡ ΡΠ° ΡΡΠΊΠ°Π²ΠΎΠΌΡ ΠΏΡΠΎΠ΅ΠΊΡΡ Π· ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ Π΄Π»Ρ Π³ΡΡΠΏΠΈ ΠΊΠΎΠΌΠΏΠ°Π½ΡΠΉ ΠΠΏΡΡΠ΅Π½ΡΡ.
ΠΠ±ΠΎΠ²'ΡΠ·ΠΊΠΈ
Β· ΠΠ±ΡΡ ΡΠ° ΡΠΎΡΠΌΠ°Π»ΡΠ·Π°ΡΡΡ Π²ΠΈΠΌΠΎΠ³ Π΄ΠΎ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΡ Π΄Π°Π½ΠΈΡ , ΡΡ ΡΡΡΡΠΊΡΡΡΠΈ ΡΠ° ΡΠΏΠ΅ΡΠΈΡΡΠΊΠΈ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ. Π£Π·Π³ΠΎΠ΄ΠΆΠ΅Π½Π½Ρ Π²ΠΈΠΌΠΎΠ³ Π· Π·Π°ΡΡΠΊΠ°Π²Π»Π΅Π½ΠΈΠΌΠΈ ΡΡΠΎΡΠΎΠ½Π°ΠΌΠΈ.
Β· ΠΠ±ΡΡ, Π²ΠΈΠ²ΡΠ΅Π½Π½Ρ ΡΠ° ΡΡΡΡΠΊΡΡΡΡΠ²Π°Π½Π½Ρ Π²ΠΈΠΌΠΎΠ³ Π΄Π»Ρ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ DWH, ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ DWH
Β· ΠΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ ETL-ΠΏΡΠΎΡΠ΅ΡΡΠ²
Β· Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΠΏΡΠΎΡΠ΅ΡΡΠ² ΡΠ° ΡΠΏΠ΅ΡΠΈΡΡΠΊΠ°ΡΡΠΉ ΠΎΠ±ΠΌΡΠ½Ρ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡΡ Π· Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½ΡΠΌ RabbitMQ, API
Β· ΠΠΎΡΡΠ°Π½ΠΎΠ²ΠΊΠ° Π·Π°Π΄Π°ΡΡ ΡΠΎΠ·ΡΠΎΠ±Π½ΠΈΠΊΠ°ΠΌ Ρ ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ Π²ΠΈΠΌΠΎΠ³Π°ΠΌΠΈ Π² Jira
Β· ΠΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠ΅Π°Π»ΡΠ·Π°ΡΡΡ Π²ΠΈΠΌΠΎΠ³ ΡΠΎΠ·ΡΠΎΠ±Π½ΠΈΠΊΠ°ΠΌΠΈ
Β· ΠΠΎΠΊΡΠΌΠ΅Π½ΡΡΠ²Π°Π½Π½Ρ ΡΠ΅ΡΠ²ΡΡΡΠ² (DHW, ETL, DataQuality, OLAP, BI, ΡΠ΅ΡΠ²ΡΡΠΈ ERP ΡΠΈΡΡΠ΅ΠΌΠΈ, ΠΏΠΎΠ²βΡΠ·Π°Π½Ρ Π· Π°Π½Π°Π»ΡΡΠΈΠΊΠΎΡ ΡΠ° ΠΏΡΠΎΠ³Π½ΠΎΠ·ΡΠ²Π°Π½Π½ΡΠΌ)
Β· ΠΠ±ΡΡ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡ, ΠΎΠΏΠΈΡ ΡΠ° ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΡΠ²
Β· ΠΠ½Π°Π»ΡΠ· Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΡΠ° ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΠΏΡΠΎΠΏΠΎΠ·ΠΈΡΡΠΉ Π· ΠΏΠΎΠΊΡΠ°ΡΠ΅Π½Π½Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ²
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Β· 265 views Β· 43 applications Β· 5d
Data analyst
Hybrid Remote Β· Ukraine (Kyiv) Β· Product Β· 2 years of experience Β· B1 - IntermediateΠΡΠΈΠ²ΡΡ! ΠΠ°ΡΠΌΠΎ ΡΡΠ΄ΠΎΠ²Ρ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π΄Π»Ρ ΡΠ΅Π±Π΅ Π΄ΠΎΠ»ΡΡΠΈΡΠΈΡΡ Π΄ΠΎ ΠΎΠ΄Π½ΠΎΠ³ΠΎ Π· Π½Π°ΡΠΈΡ ΡΡΡΡΠΌΠΊΠΎ Π·ΡΠΎΡΡΠ°ΡΡΠΈΡ Π±ΡΠ·Π½Π΅ΡΡΠ², ΡΠΊΠΈΠΉ ΠΏΡΠ°ΡΡΡ Π½Π°Π΄ social ΠΏΡΠΎΠ΄ΡΠΊΡΠ°ΠΌΠΈ Ρ ΡΡΠ΅ΡΡ Π²ΡΠ΄Π΅ΠΎΡΡΡΡΠΌΡΠ½Π³Ρ! ΠΠΎΠ΄Π°ΡΠΊΠΈ, ΡΠΊΡ Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΡΡΡ Π½Π°ΡΡ ΡΡΡΠ΅Π½Π½Ρ Π²ΠΆΠ΅ Π²Ρ ΠΎΠ΄ΡΡΡ Ρ ΡΠΎΠΏ ΡΠ²ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΌΠ΅Π½ΡΡ, Π°ΠΊΡΠΈΠ²Π½ΠΎ ΠΏΠΎΡΠΈΡΡΡΡΡΡΡ...ΠΡΠΈΠ²ΡΡ!
ΠΠ°ΡΠΌΠΎ ΡΡΠ΄ΠΎΠ²Ρ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ Π΄Π»Ρ ΡΠ΅Π±Π΅ Π΄ΠΎΠ»ΡΡΠΈΡΠΈΡΡ Π΄ΠΎ ΠΎΠ΄Π½ΠΎΠ³ΠΎ Π· Π½Π°ΡΠΈΡ ΡΡΡΡΠΌΠΊΠΎ Π·ΡΠΎΡΡΠ°ΡΡΠΈΡ Π±ΡΠ·Π½Π΅ΡΡΠ², ΡΠΊΠΈΠΉ ΠΏΡΠ°ΡΡΡ Π½Π°Π΄ social ΠΏΡΠΎΠ΄ΡΠΊΡΠ°ΠΌΠΈ Ρ ΡΡΠ΅ΡΡ Π²ΡΠ΄Π΅ΠΎΡΡΡΡΠΌΡΠ½Π³Ρ!
ΠΠΎΠ΄Π°ΡΠΊΠΈ, ΡΠΊΡ Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΡΡΡ Π½Π°ΡΡ ΡΡΡΠ΅Π½Π½Ρ Π²ΠΆΠ΅ Π²Ρ ΠΎΠ΄ΡΡΡ Ρ ΡΠΎΠΏ ΡΠ²ΠΎΠ³ΠΎ ΡΠ΅Π³ΠΌΠ΅Π½ΡΡ, Π°ΠΊΡΠΈΠ²Π½ΠΎ ΠΏΠΎΡΠΈΡΡΡΡΡΡΡ ΠΏΠΎ Π²ΡΡΠΎΠΌΡ ΡΠ²ΡΡΡ Ρ ΠΌΠ°ΡΡΡ ΠΏΠΎΠ½Π°Π΄ 10 ΠΌΡΠ»ΡΠΉΠΎΠ½ΡΠ² Π·Π°Π²Π°Π½ΡΠ°ΠΆΠ΅Π½Ρ. ΠΠΈ Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΡΡΠΌΠΎ ΠΏΠ΅ΡΠ΅Π΄ΠΎΠ²Ρ ΡΠ΅Ρ Π½ΠΎΠ»ΠΎΠ³ΡΡ peer-to-peer Π°ΡΠ΄ΡΠΎ ΡΠ° Π²ΡΠ΄Π΅ΠΎΠ·Π²βΡΠ·ΠΊΡ, ΡΠΊΡ Π²ΠΈΠΊΠΎΡΠΈΡΡΠΎΠ²ΡΡΡΡΡΡ Π² ΡΠ°ΠΊΠΈΡ Π΄ΠΎΠ΄Π°ΡΠΊΠ°Ρ , ΡΠΊ Telegram, WhatsApp ΡΠ° Google Meet.
ΠΠ°ΡΠ° ΠΊΠΎΠΌΠ°Π½Π΄Π° Π°ΠΊΡΠΈΠ²Π½ΠΎ Π·ΡΠΎΡΡΠ°Ρ, ΡΠΎΠΌΡ ΡΡΠΊΠ°ΡΠΌΠΎ Data analyst.
βοΈΠΠΊΡΠΈΠ²Π½ΠΎ ΡΠΎΠ·Π³Π»ΡΠ΄Π°ΡΠΌΠΎ ΡΠ²ΡΡΡΠ΅ΡΡΠ².
βοΈΠΠΎΠ·ΠΈΡΡΡ ΠΏΠ΅ΡΠ΅Π΄Π±Π°ΡΠ°Ρ ΡΠΎΠ±ΠΎΡΡ Π² Π³ΡΠ±ΡΠΈΠ΄Π½ΠΎΠΌΡ ΡΠΎΡΠΌΠ°ΡΡ Π· ΠΎΡΡΡΡ Π² ΠΠΈΡΠ²Ρ.
ΠΠ°Π΄Π°ΡΡ:
β ΠΠΏΡΠΈΠΌΡΠ·ΠΎΠ²ΡΠ²Π°ΡΠΈ Π°Π½Π°Π»ΡΡΠΈΡΠ½Ρ ΠΏΡΠΎΡΠ΅ΡΠΈ ΡΠ»ΡΡ ΠΎΠΌ Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ ΠΏΠ΅ΡΠ΅Π΄ΠΎΠ²ΠΈΡ ΠΏΡΠ°ΠΊΡΠΈΠΊ, Π½ΠΎΠ²ΠΈΡ ΠΏΡΠ΄Ρ ΠΎΠ΄ΡΠ² ΡΠ° ΡΡΡΠ°ΡΠ½ΠΈΡ ΡΠ½ΡΡΡΡΠΌΠ΅Π½ΡΡΠ² Ρ ΡΠΎΠ±ΠΎΡΡ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ;
β ΠΠΏΡΠΎΠ²Π°Π΄ΠΆΡΠ²Π°ΡΠΈ ΡΡΡΠ΅Π½Π½Ρ Π΄Π»Ρ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·Π°ΡΡΡ ΡΠ° ΠΎΠΏΡΠΈΠΌΡΠ·Π°ΡΡΡ;
β ΠΡΠΎΠ²ΠΎΠ΄ΠΈΡΠΈ Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ Π½Π° ΠΎΡΠ½ΠΎΠ²Ρ ΡΡΠ½ΡΡΡΠΎΡ Π·Π²ΡΡΠ½ΠΎΡΡΡ;
β ΠΡΠΎΠ²ΠΎΠ΄ΠΈΡΠΈ ad hoc-Π°Π½Π°Π»ΡΠ·ΠΈ ΡΠ° ΡΠ΅ΡΡΡΠ²Π°ΡΠΈ Π³ΡΠΏΠΎΡΠ΅Π·ΠΈ.Π©ΠΎ Π΄Π»Ρ Π½Π°Ρ Π²Π°ΠΆΠ»ΠΈΠ²ΠΎ:
β ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π½Π° Π°Π½Π°Π»ΠΎΠ³ΡΡΠ½ΡΠΉ ΠΏΠΎΡΠ°Π΄Ρ Π²ΡΠ΄ 1 ΡΠΎΠΊΡ;
β ΠΠΏΠ΅Π²Π½Π΅Π½Π΅ Π·Π½Π°Π½Π½Ρ SQL;
β ΠΠ½Π°Π»ΡΡΠΈΡΠ½Π΅ ΠΌΠΈΡΠ»Π΅Π½Π½Ρ ΡΠ° ΠΏΡΠ°Π³Π½Π΅Π½Π½Ρ Π΄ΠΎ Π½Π΅ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΠΈΡ ΡΡΡΠ΅Π½Ρ;
β ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· Python;
β ΠΠ°ΠΆΠ°Π½Π½Ρ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π· ML.Π©ΠΎ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
β ΠΡΠ±ΡΠΈΠ΄Π½ΠΈΠΉ ΡΠΎΡΠΌΠ°Ρ ΡΠΎΠ±ΠΎΡΠΈ Π² Π½ΠΎΠ²ΠΎΠΌΡ Π°Π²ΡΠΎΠ½ΠΎΠΌΠ½ΠΎΠΌΡ ΠΎΡΡΡΡ Π·Ρ ΡΠ½ΡΠ΄Π°Π½ΠΊΠ°ΠΌΠΈ, ΠΎΠ±ΡΠ΄Π°ΠΌΠΈ ΡΠ° ΡΠ½Π΅ΠΊΠ°ΠΌΠΈ;
β 4 ΡΠΈΠΆΠ½Ρ ΠΎΠΏΠ»Π°ΡΡΠ²Π°Π½ΠΎΡ Π²ΡΠ΄ΠΏΡΡΡΠΊΠΈ Π½Π° ΡΡΠΊ Ρ Π±Π΅Π·Π»ΡΠΌΡΡΠ½Ρ sick-leave days;
β ΠΠΎΡΡΡΠΏ Π΄ΠΎ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½ΠΎΠ³ΠΎ Π»ΡΠΊΠ°ΡΡ ΡΠ° ΠΌΠ΅Π΄ΠΈΡΠ½Π΅ ΡΡΡΠ°Ρ ΡΠ²Π°Π½Π½Ρ;
β ΠΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ ΠΊΡΡΡΡΠ² Π°Π½Π³Π»ΡΠΉΡΡΠΊΠΎΡ ΡΠ° Π½Π°Π²ΡΠ°Π»ΡΠ½ΠΈΡ ΠΏΡΠΎΠ³ΡΠ°ΠΌ;
β ΠΠΎΡΡΡΠΏ Π΄ΠΎ Π²Π½ΡΡΡΡΡΠ½ΡΡ ΡΠΊΡΠ», Π½Π°Π²ΡΠ°Π»ΡΠ½ΠΈΡ ΡΠ²Π΅Π½ΡΡΠ² ΡΠ° ΠΏΠΎΠ½Π°Π΄ 1000 ΠΊΡΡΡΡΠ², Π»Π΅ΠΊΡΡΠΉ Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠ½Π½ΠΈΡ ΠΊΠ½ΠΈΠ³ Π½Π° ΡΡΠ·Π½ΠΎΠΌΠ°Π½ΡΡΠ½Ρ ΡΠ΅ΠΌΠΈ.Π―ΠΊΡΠΎ ΡΠΈ ΡΡΠΊΠ°ΡΡ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π·Ρ ΡΠΊΠ»Π°Π΄Π½ΠΈΠΌΠΈ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΠΌΠΈ Π·Π°Π΄Π°ΡΠ°ΠΌΠΈ, ΠΎΠ±ΡΠΎΠ±Π»ΡΡΠΈ Π²Π΅Π»ΠΈΠΊΡ Π΄Π°Π½Ρ, ΡΡ ΠΏΠΎΠ·ΠΈΡΡΡ β ΡΠ°ΠΌΠ΅ ΡΠ΅, ΡΠΎ ΡΠΎΠ±Ρ ΠΏΠΎΡΡΡΠ±Π½ΠΎ! ΠΠ°Π΄ΡΠΈΠ»Π°ΠΉ CV :)
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Β· 32 views Β· 4 applications Β· 27d
Senior finance manager
Full Remote Β· EU Β· Product Β· 3 years of experienceΠΠΈ β iGaming ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Π· Π±ΡΠ»ΡΡ Π½ΡΠΆ ΡΡΠΈΡΡΡΠ½ΠΈΠΌ Π΄ΠΎΡΠ²ΡΠ΄ΠΎΠΌ ΡΠΎΠ±ΠΎΡΠΈ ΡΠ° ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ, ΡΠΊΠ° ΡΠΊΠ»Π°Π΄Π°ΡΡΡΡΡ Π· ΠΏΠΎΠ½Π°Π΄ 1300+ ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΡΠ². ΠΠ°ΡΡ Π΄ΠΎΡΡΠ³Π½Π΅Π½Π½Ρ Π²ΠΊΠ»ΡΡΠ°ΡΡΡ 10+ Π²Π΅Π»ΠΈΠΊΠΈΡ ΠΏΡΠΎΠ΅ΠΊΡΡΠ², ΡΠΊΡ ΠΊΠΎΡΠΈΡΡΡΡΡΡΡΡ ΠΏΠΎΠΏΡΠ»ΡΡΠ½ΡΡΡΡ ΡΠ΅ΡΠ΅Π΄ Π½Π°ΡΠΈΡ ΠΊΠ»ΡΡΠ½ΡΡΠ² ΡΠ° ΡΡΠΏΡΡΠ½ΠΎ ΠΏΡΠ°ΡΡΡΡΡ Ρ Π»ΠΎΠΊΠ°ΡΡΡΡ ΠΊΡΠ°ΡΠ½...ΠΠΈ β iGaming ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ Π· Π±ΡΠ»ΡΡ Π½ΡΠΆ ΡΡΠΈΡΡΡΠ½ΠΈΠΌ Π΄ΠΎΡΠ²ΡΠ΄ΠΎΠΌ ΡΠΎΠ±ΠΎΡΠΈ ΡΠ° ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ, ΡΠΊΠ° ΡΠΊΠ»Π°Π΄Π°ΡΡΡΡΡ Π· ΠΏΠΎΠ½Π°Π΄ 1300+ ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΡΠ².
ΠΠ°ΡΡ Π΄ΠΎΡΡΠ³Π½Π΅Π½Π½Ρ Π²ΠΊΠ»ΡΡΠ°ΡΡΡ 10+ Π²Π΅Π»ΠΈΠΊΠΈΡ ΠΏΡΠΎΠ΅ΠΊΡΡΠ², ΡΠΊΡ ΠΊΠΎΡΠΈΡΡΡΡΡΡΡΡ ΠΏΠΎΠΏΡΠ»ΡΡΠ½ΡΡΡΡ ΡΠ΅ΡΠ΅Π΄ Π½Π°ΡΠΈΡ ΠΊΠ»ΡΡΠ½ΡΡΠ² ΡΠ° ΡΡΠΏΡΡΠ½ΠΎ ΠΏΡΠ°ΡΡΡΡΡ Ρ Π»ΠΎΠΊΠ°ΡΡΡΡ ΠΊΡΠ°ΡΠ½ Tier 1-3.
ΠΠΎΠΌΠΏΠ°Π½ΡΡ Π·Π°Π»ΡΡΠ°Ρ ΡΠ° ΡΡΠ½ΡΡ Π²ΠΈΡΠΎΠΊΠΎΠΊΠ²Π°Π»ΡΡΡΠΊΠΎΠ²Π°Π½ΠΈΡ ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΡΠ², ΡΠΎ Π΄ΠΎΠ·Π²ΠΎΠ»ΡΡ Π½Π°ΠΌ Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎ Π±ΡΠ΄ΡΠ²Π°ΡΠΈ ΠΏΡΠΎΡΠ΅ΡΠΈ ΡΠ° ΡΡΠΏΡΡΠ½ΠΎ ΡΠΎΠ·ΡΠΈΡΡΠ²Π°ΡΠΈ Π½Π°ΡΡ ΠΏΡΠΈΡΡΡΠ½ΡΡΡΡ Π½Π° Π½ΠΎΠ²ΠΈΡ Π»ΠΎΠΊΠ°ΡΡΡΡ .Π‘ΡΠ°Π½ΡΡΠ΅ ΡΠ°ΡΡΠΈΠ½ΠΎΡ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ, ΡΠΊΠ° Π·Π°ΠΏΡΡΠΊΠ°Ρ Π½ΠΎΠ²Ρ ΠΏΡΠΎΠ΅ΠΊΡΠΈ Π½Π° ΡΡΠ·Π½ΠΈΡ ΡΠΈΠ½ΠΊΠ°Ρ ΡΠ° ΡΠΎΡΠΌΡΡ ΠΌΠ°ΠΉΠ±ΡΡΠ½Ρ iGaming ΡΠ½Π΄ΡΡΡΡΡΡ.
Π’Π²ΠΎΡ ΠΌΠ΅ΡΠ° -Π·Π°Π±Π΅Π·ΠΏΠ΅ΡΠ΅Π½Π½Ρ ΡΠΎΡΠ½ΠΎΡΡΡ, ΡΠ²ΠΎΡΡΠ°ΡΠ½ΠΎΡΡΡ ΡΠ° ΠΏΠΎΠ²Π½ΠΎΡΠΈ ΡΠΎΠ·Π½Π΅ΡΠ΅Π½Π½Ρ Π²ΠΈΠΏΠΈΡΠΎΠΊ Π· ΠΏΠ»Π°ΡΡΠΆΠ½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌ (PSP). ΠΡΠΎΠ²Π΅Π΄Π΅Π½Π½Ρ ΡΠ΅Π³ΡΠ»ΡΡΠ½ΠΈΡ Π·Π²ΡΡΠΎΠΊ ΡΠ° ΠΊΠΎΠ½ΡΡΠΎΠ»Ρ Π·Π° ΠΊΠΎΡΠ΅ΠΊΡΠ½ΡΡΡΡ Π±Π°Π»Π°Π½ΡΠΎΠ²ΠΈΡ Π·Π°Π»ΠΈΡΠΊΡΠ².
ΠΡΠ½ΠΎΠ²Π½Ρ ΠΎΠ±ΠΎΠ²βΡΠ·ΠΊΠΈ:
- ΠΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° ΡΠ° Π·Π°Ρ ΠΈΡΡ ΡΠΏΡΠ°Π²Π»ΡΠ½ΡΡΠΊΠΎΡ Π·Π²ΡΡΠ½ΠΎΡΡΡ (P&L, Cash Flow, Balance Sheet).
- ΠΠ»Π°Π½ΡΠ²Π°Π½Π½Ρ ΡΠ° Π±ΡΠ΄ΠΆΠ΅ΡΡΠ²Π°Π½Π½Ρ.
- ΠΡΠ΄Π³ΠΎΡΠΎΠ²ΠΊΠ° ΠΌΡΡΡΡΠ½ΠΈΡ , ΠΊΠ²Π°ΡΡΠ°Π»ΡΠ½ΠΈΡ Ρ ΡΡΡΠ½ΠΈΡ ΡΡΠ½Π°Π½ΡΠΎΠ²ΠΈΡ Π·Π²ΡΡΡΠ²
- ΠΠΎΠ½ΡΡΠΎΠ»Ρ ΠΠ‘Π.
- ΠΠ½Π°Π»ΡΠ· Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ Π²ΠΈΡΡΠ°Ρ Ρ ΠΏΡΠΎΠΏΠΎΠ·ΠΈΡΡΡ ΠΏΠΎ ΡΡ Π·Π½ΠΈΠΆΠ΅Π½Π½Ρ.
ΠΠΎΠ½ΡΡΠΎΠ»Ρ ΡΠΎΠ·ΡΠ°Ρ ΡΠ½ΠΊΡ ΡΠ° Π²ΠΈΠΏΠ»Π°ΡΠΈ Π·Π°ΡΠΎΠ±ΡΡΠ½ΠΎΡ ΠΏΠ»Π°ΡΠΈ (ΡΡΠ°Π²ΠΊΠ° + ΡΠ°ΡΡΠΈΠ½Π° KPI).
ΠΠΈΠΌΠΎΠ³ΠΈ Π΄ΠΎ ΠΊΠ°Π½Π΄ΠΈΠ΄Π°ΡΠ°:
- 3β5 ΡΠΎΠΊΡΠ² Π΄ΠΎΡΠ²ΡΠ΄Ρ ΡΠΎΠ±ΠΎΡΠΈ Ρ ΡΡΠ½Π°Π½ΡΠΎΠ²ΡΠΉ ΡΡΠ΅ΡΡ.
- ΠΠΏΠ΅Π²Π½Π΅Π½Π΅ Π²ΠΎΠ»ΠΎΠ΄ΡΠ½Π½Ρ Excel / Google Docs.
- ΠΠΎΡΠ²ΡΠ΄ ΠΎΠ±ΡΠΎΠ±ΠΊΠΈ Π²Π΅Π»ΠΈΠΊΠΈΡ ΠΎΠ±ΡΡΠ³ΡΠ² Π΄Π°Π½ΠΈΡ .
- ΠΠΎΡΠ²ΡΠ΄ ΡΠΎΠ±ΠΎΡΠΈ Π· PSP.
- ΠΠΎΡΠ²ΡΠ΄ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ²ΠΈ ΡΠΏΡΠ°Π²Π»ΡΠ½ΡΡΠΊΠΎΡ Π·Π²ΡΡΠ½ΠΎΡΡΡ.
- ΠΠΎΡΠ²ΡΠ΄ Π² ΠΌΠ΅Π½ΡΠΎΡΡΡΠ²Ρ ΡΠ° ΡΠΏΡΠ°Π²Π»ΡΠ½Π½Ρ Π΄Π΅ΠΊΡΠ»ΡΠΊΠΎΠΌΠ° ΠΌΠ΅Π½Π΅Π΄ΠΆΠ΅ΡΠ°ΠΌΠΈ.
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Β· 80 views Β· 10 applications Β· 10d
Senior Data Analyst
Worldwide Β· Product Β· 2 years of experience Β· B1 - IntermediateΠΡΠΈΠ²ΡΡ! Π¨ΡΠΊΠ°ΡΠΌΠΎ Senior Data Analyst, ΡΠΊΠΈΠΉ Π½Π΅ ΠΏΡΠΎΡΡΠΎ Π·Π²ΠΎΠ΄ΠΈΡΡ Π΄Π°Π½Ρ β Π° Π±Π°ΡΠΈΡΡ Ρ Π½ΠΈΡ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ Π΄Π»Ρ ΡΠΎΡΡΡ Π―ΠΊΡΠΎ ΡΠ΅Π±Π΅ Π΄ΡΠ°ΠΉΠ²ΠΈΡΡ Π·Π½Π°Ρ ΠΎΠ΄ΠΈΡΠΈ ΡΠΎΡΠΊΠΈ ΠΌΠ°ΡΡΡΠ°Π±ΡΠ²Π°Π½Π½Ρ, Π±ΡΠ΄ΡΠ²Π°ΡΠΈ Π³Π½ΡΡΠΊΡ Π°Π½Π°Π»ΡΡΠΈΡΠ½Ρ ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΡ ΡΠ° Π²ΠΏΠ»ΠΈΠ²Π°ΡΠΈ Π½Π° ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³ ΡΠ΅ΡΠ΅Π· ΡΠΈΡΡΠΈ β ΡΠ΅ ΡΠ°ΠΌΠ΅ ΡΠΎΠΉ Π²ΠΈΠΊΠ»ΠΈΠΊ,...ΠΡΠΈΠ²ΡΡ!
Π¨ΡΠΊΠ°ΡΠΌΠΎ Senior Data Analyst, ΡΠΊΠΈΠΉ Π½Π΅ ΠΏΡΠΎΡΡΠΎ Π·Π²ΠΎΠ΄ΠΈΡΡ Π΄Π°Π½Ρ β Π° Π±Π°ΡΠΈΡΡ Ρ Π½ΠΈΡ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ Π΄Π»Ρ ΡΠΎΡΡΡ π
Π―ΠΊΡΠΎ ΡΠ΅Π±Π΅ Π΄ΡΠ°ΠΉΠ²ΠΈΡΡ Π·Π½Π°Ρ ΠΎΠ΄ΠΈΡΠΈ ΡΠΎΡΠΊΠΈ ΠΌΠ°ΡΡΡΠ°Π±ΡΠ²Π°Π½Π½Ρ, Π±ΡΠ΄ΡΠ²Π°ΡΠΈ Π³Π½ΡΡΠΊΡ Π°Π½Π°Π»ΡΡΠΈΡΠ½Ρ ΡΠ½ΡΡΠ°ΡΡΡΡΠΊΡΡΡΡ ΡΠ° Π²ΠΏΠ»ΠΈΠ²Π°ΡΠΈ Π½Π° ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³ ΡΠ΅ΡΠ΅Π· ΡΠΈΡΡΠΈ β ΡΠ΅ ΡΠ°ΠΌΠ΅ ΡΠΎΠΉ Π²ΠΈΠΊΠ»ΠΈΠΊ, ΡΠΊΠΎΠ³ΠΎ ΡΠΈ ΡΠ΅ΠΊΠ°Π².
ΠΠΈ, Honeytech β Π΄ΠΈΠ½Π°ΠΌΡΡΠ½ΠΈΠΉ, ΡΠ²ΠΈΠ΄ΠΊΠΎΠ·ΡΠΎΡΡΠ°ΡΡΠΈΠΉ ΠΏΡΠΎΠ΅ΠΊΡ, ΡΠΎ Π²ΠΆΠ΅ Π·Π°ΠΉΠΌΠ°Ρ ΠΎΠ΄Π½Ρ Π· Π»ΡΠ΄Π΅ΡΡΡΠΊΠΈΡ ΠΏΠΎΠ·ΠΈΡΡΠΉ Ρ ΡΠ²ΡΡΡ Π²Π΅Π±ΠΊΠΎΠΌΡΠΊΡΡΠ². ΠΠ° ΠΎΡΡΠ°Π½Π½Ρ 3 ΡΠΎΠΊΠΈ ΠΌΠΈ Π·ΡΠ±ΡΠ°Π»ΠΈ ΠΊΠΎΠΌΠ°Π½Π΄Ρ ΡΠΈΠ»ΡΠ½ΠΈΡ ΡΠΏΠ΅ΡΡΠ°Π»ΡΡΡΡΠ², Π· ΡΠΊΠΈΠΌΠΈ Π²ΠΈΡΠΎΡΠ»ΠΈ Ρ 10+ ΡΠ°Π·ΡΠ² ΡΠ° ΠΏΠ»Π°Π½ΡΡΠΌΠΎ Π²ΠΈΡΠΎΡΡΠΈ ΡΠ΅ Π² ΡΡΠΈΡΡ ΡΡΠΎΠ³ΠΎ ΡΠΎΠΊΡ, ΡΠΎΠΌΡ Π·Π°ΡΠ°Π· ΡΡΠΊΠ°ΡΠΌΠΎ Π½ΠΎΠ²ΠΎΠ³ΠΎ Π°ΠΌΠ±ΡΡΠ½ΠΎΠ³ΠΎ ΡΠ° ΠΏΡΠΎΠ°ΠΊΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΊΠΎΠ»Π΅Π³Ρ. ΠΠΈ Π²ΠΆΠ΅ ΡΡΠΈΠ²Π°Π»ΠΈΠΉ ΡΠ°Ρ ΠΏΡΠΈΠ±ΡΡΠΊΠΎΠ²Ρ ΡΠ° Π·Π½Π°Ρ ΠΎΠ΄ΠΈΠΌΠΎΡΡ Π½Π° Π΅ΡΠ°ΠΏΡ ΠΌΠ°ΡΡΡΠ°Π±ΡΠ²Π°Π½Π½Ρ.
- ΠΠΈ ΡΠ΄ΠΈΠ½Π° Ρ ΡΠ²ΡΡΡ Π½Π΅ Π°Π·ΡΠΉΡΡΠΊΠ° Π²Π΅ΡΡΠΈΠΊΠ°Π»ΡΠ½ΠΎ ΡΠ½ΡΠ΅Π³ΡΠΎΠ²Π°Π½Π° ΠΏΠ»Π°ΡΡΠΎΡΠΌΠ° Π· Π²ΠΈΡΠΎΠ±Π½ΠΈΡΡΠ²Π° ΡΠ° Π΄ΠΈΡΡΡΠΈΠ±ΡΡΡΡ webtoon
- Π’ΠΈ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈΠΌΠ΅Ρ Π· ΠΊΠΎΠ»Π΅Π³Π°ΠΌΠΈ-Π°Π½Π°Π»ΡΡΠΈΠΊΠ°ΠΌΠΈ senior ΡΡΠ²Π½Ρ + ΠΊΠΎΠΌΠ°Π½Π΄ΠΎΡ Π· ΡΠΈΠ»ΡΠ½ΠΎΡ Π΅ΠΊΡΠΏΠ΅ΡΡΠΈΠ·ΠΎΡ Π² ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³Ρ ΡΠ° Π±ΡΠ·Π½Π΅Ρ Π΄Π΅Π²Π΅Π»ΠΎΠΏΠΌΠ΅Π½ΡΡ.
- ΠΠ°ΡΠΌΠΎ ΠΌΡΠ½ΡΠΌΡΠΌ Π±ΡΡΠΎΠΊΡΠ°ΡΡΡ, ΠΌΠ°ΠΊΡΠΈΠΌΡΠΌ ΡΠ°ΠΌΠΎΡΡΡΠΉΠ½ΠΎΡΡΡ, ΡΠ²ΠΎΠ±ΠΎΠ΄ΠΈ Π΄ΡΠΉ ΡΠ° Π²ΠΈΡΠΎΠΊΠΎΡ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π°Π»ΡΠ½ΠΎΡΡΡ.
- ΠΠ°Ρ Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΠΉ ΡΡΠ΅ΠΊ: Bigquery + Tableau + Amplitude
- ΠΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ ΠΊΠΎΠΌΡΠΎΡΡΠ½Ρ ΡΠΌΠΎΠ²ΠΈ Π΄Π»Ρ ΡΠΎΠ±ΠΎΡΠΈ: remote Π°Π±ΠΎ ΠΎΡΡΡ (ΠΠΈΡΠ² / ΠΠ°ΡΡΠ°Π²Π°) Π½Π° Π²ΠΈΠ±ΡΡ ΡΠ° ΠΏΠΎΠ²Π½ΠΈΠΉ ΡΠΎΡΠΏΠ°ΠΊΠ΅Ρ.
ΠΠ° ΡΡΠΉ ΠΏΠΎΠ·ΠΈΡΡΡ ΠΏΠΎΡΡΡΠ±Π½ΠΎ Π»ΡΠ΄ΠΈΡΠΈ ΡΡΠ½ΠΊΡΡΡ ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³ Π°Π½Π°Π»ΡΡΠΈΠΊΠΈ ΡΠ° Π·Π°ΠΉΠΌΠ°ΡΠΈΡΡ Π½Π°ΡΡΡΠΏΠ½ΠΈΠΌΠΈ Π·Π°Π΄Π°ΡΠ°ΠΌΠΈ:
- ΠΠ½Π°Ρ ΠΎΠ΄ΠΈΡΠΈ ΡΠΎΡΠΊΠΈ ΡΠΎΡΡΡ Π½Π° ΡΡΠΎΡΠΎΠ½Ρ ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³Ρ.
- ΠΡΠ΄ΡΡΠΈΠΌΡΠ²Π°ΡΠΈ ΡΠΈΡΡΠ΅ΠΌΡ ΠΎΡΡΠ½ΠΊΠΈ ΠΌΠ°ΡΠΊΠ΅ΡΠΈΠ½Π³Ρ.
- ΠΠ±ΠΈΡΠ°ΡΠΈ ΡΠ° Π½Π°Π»Π°ΡΡΠΎΠ²ΡΠ²Π°ΡΠΈ ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½Ρ Π°ΡΡΠΈΠ±ΡΡΡΡ.
- ΠΡΠ΄ΡΠ²Π°ΡΠΈ ΡΠ° ΡΠ΄ΠΎΡΠΊΠΎΠ½Π°Π»ΡΠ²Π°ΡΠΈ Π·Π²ΡΡΠ½ΠΎΡΡΡ Π² Tableau.
- Π‘ΡΠ°Π²ΠΈΡΠΈ Π’Π Π΄Π»Ρ ΡΡΠ΅ΠΊΡΠ½Π³Ρ ΡΠ° ΡΡΠ²ΠΎΡΠ΅Π½Π½Ρ ΡΠΈΡΡΠ΅ΠΌΠΈ ΡΡ ΠΏΠ΅ΡΠ΅Π²ΡΡΠΊΠΈ.
- Π ΠΎΠ·ΡΠΎΠ±Π»ΡΠ²Π°ΡΠΈ ΡΠ° Π°Π²ΡΠΎΠΌΠ°ΡΠΈΠ·ΠΎΠ²ΡΠ²Π°ΡΠΈ data pipelines.
- ΠΠ΅Π½ΡΠΎΡΠΈΡΠΈ ΠΉ ΠΌΠ΅Π½Π΅Π΄ΠΆΠ΅ΡΠΈΡΠΈ ΠΌΠΎΠ»ΠΎΠ΄ΡΠΈΡ ΠΊΠΎΠ»Π΅Π³.
ΠΠΎΠ³ΠΎ ΡΠ°ΠΌΠ΅ ΡΡΠΊΠ°ΡΠΌΠΎ?
Π’Π΅Ρ Π½ΡΡΠ½Ρ Π½Π°Π²ΠΈΡΠΊΠΈ:
- 2 ΡΠΎΠΊΠΈ+ Π΄ΠΎΡΠ²ΡΠ΄Ρ ΡΠΎΠ±ΠΎΡΠΈ Π΄Π°ΡΠ° Π°Π½Π°Π»ΡΡΠΈΠΊΠΎΠΌ/data scientist Π² IT ΠΊΠΎΠΌΠΏΠ°Π½ΡΡΡ .
- ΠΡΠΎΡΠ΅ΡΡΠΉΠ½ΠΈΠΉ SQL (Π΄ΠΎΡΠ²ΡΠ΄ Π· BigQuery Π±ΡΠ΄Π΅ ΠΏΠ΅ΡΠ΅Π²Π°Π³ΠΎΡ).
- ΠΠ½Π°Π½Π½Ρ Python (pandas, numpy) ΠΏΡΠΈΠ½Π°ΠΉΠΌΠ½Ρ Π½Π° ΡΠ΅ΡΠ΅Π΄Π½ΡΠΎΠΌΡ ΡΡΠ²Π½Ρ.
- ΠΠ½Π°Π½Π½Ρ ΡΡΠ°ΡΠΈΡΡΠΈΠΊΠΈ ΡΠ° ΡΠ΅ΠΎΡΡΡ ΠΉΠΌΠΎΠ²ΡΡΠ½ΠΎΡΡΡ.
- ΠΠ½Π°Π½Π½Ρ ΡΠ΅ΠΎΡΡΡ ΠΎΡΡΠ½ΠΊΠΈ AB ΡΠ΅ΡΡΡΠ².
- ΠΠΎΡΠ²ΡΠ΄ ΠΏΠΎΠ±ΡΠ΄ΠΎΠ² Π°Π½Π°Π»ΡΡΠΈΡΠ½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ.
- Π ΠΎΠ·ΡΠΌΡΠ½Π½Ρ ΠΏΡΠ΄Ρ ΠΎΠ΄ΡΠ² ΠΊΠΎΠ³ΠΎΡΡΠ½ΠΎΠ³ΠΎ Π°Π½Π°Π»ΡΠ·Ρ.
Π ΠΈΡΠΈ, Π½Π° ΡΠΊΡ ΠΌΠΈ Π·Π²Π΅ΡΡΠ°ΡΠΌΠΎ ΡΠ²Π°Π³Ρ:
- ΠΠ½Π΅ΡΠ³ΡΠΉΠ½ΡΡΡΡ β Π²Π΅Π»ΠΈΠΊΡ ΠΎΠ±ΡΡΠ³ΠΈ ΡΠΎΠ±ΠΎΡΠΈ ΡΠ΅Π±Π΅ Π½Π΅ Π»ΡΠΊΠ°ΡΡΡ, Π° ΡΡΠ»ΡΠΊΠΈ ΠΌΠΎΡΠΈΠ²ΡΡΡΡ. Π’ΠΈ Π°ΠΌΠ±ΡΡΡΠΉΠ½ΠΈΠΉ Ρ ΠΆΠ°Π΄Π°ΡΡ ΡΠ²ΠΈΠ΄ΠΊΠΎΠ³ΠΎ ΡΠΎΠ·Π²ΠΈΡΠΊΡ.
- Π¦ΡΠΊΠ°Π²ΡΡΡΡ Π΄ΠΎ ΡΠ½ΡΠ°ΠΉΡΡΠ² β ΡΠΎΠ±Ρ ΡΡΠΊΠ°Π²ΠΎ Π°Π½Π°Π»ΡΠ·ΡΠ²Π°ΡΠΈ Π²Π΅Π»ΠΈΠΊΡ ΠΌΠ°ΡΠΈΠ²ΠΈ Π΄Π°Π½ΠΈΡ Π² ΠΏΠΎΡΡΠΊΠ°Ρ Π½ΠΎΠ²ΠΈΡ ΡΠ΄Π΅ΠΉ ΡΠΊ ΠΌΠΎΠΆΠ½Π° Π²ΠΏΠ»ΠΈΠ½ΡΡΠΈ Π½Π° ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΈ Π±ΡΠ·Π½Π΅ΡΡ.
- ΠΠ½Π°Π»ΡΡΠΈΡΠ½Π΅ ΠΌΠΈΡΠ»Π΅Π½Π½Ρ β ΡΠΈ ΠΊΡΠΈΡΠΈΡΠ½ΠΎ ΡΠΏΡΠΈΠΉΠΌΠ°ΡΡ ΡΠ½ΡΠΎΡΠΌΠ°ΡΡΡ Ρ ΠΌΠΎΠΆΠ΅Ρ ΠΎΠΏΠ΅ΡΡΠ²Π°ΡΠΈ ΡΠΊΠ»Π°Π΄Π½ΠΈΠΌΠΈ ΠΌΠΎΠ΄Π΅Π»ΡΠΌΠΈ.
Π―ΠΊΡΠΎ ΡΠΈ ΠΏΠΎΠ±Π°ΡΠΈΠ² Ρ ΡΡΠ΄ΠΊΠ°Ρ Π²ΠΈΡΠ΅ ΡΠ΅Π±Π΅, Π½Π°Π΄ΡΠΈΠ»Π°ΠΉ Π½Π°ΠΌ ΡΠ΅Π·ΡΠΌΠ΅ ΡΠ° ΠΏΠΎΡΠ½Π΅ΠΌΠΎ Π½Π°Ρ hiring process:
- 1ΠΉ Π΅ΡΠ°ΠΏ: Π‘ΠΏΡΠ»ΠΊΡΠ²Π°Π½Π½Ρ Π· ΡΠ΅ΠΊΡΡΡΠ΅ΡΠΎΠΌ.
- 2ΠΉ Π΅ΡΠ°ΠΏ: ΠΠ½ΡΠ΅ΡΠ²βΡ Π· ΡΡΠΌ Π»ΡΠ΄ΠΎΠΌ ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ.
- 3ΠΉ Π΅ΡΠ°ΠΏ: Π’Π΅ΡΡΠΎΠ²Π΅ Π·Π°Π²Π΄Π°Π½Π½Ρ.
- 4ΠΉ Π΅ΡΠ°ΠΏ: Π€ΡΠ½Π°Π»ΡΠ½Π΅ ΡΠ½ΡΠ΅ΡΠ²βΡ Π·Π° ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ°ΠΌΠΈ ΡΠ²ΠΎΠ³ΠΎ Π’Π.
Π Π΄Π°Π»Ρ Π½Π°Ρ ΡΠ΅ΠΊΡΡΡΠ΅Ρ Π·Π±ΠΈΡΠ°Ρ ΡΠ΅ΠΊΠΎΠΌΠ΅Π½Π΄Π°ΡΡΠΉ Π· ΠΏΠΎΠΏΠ΅ΡΠ΅Π΄Π½ΡΡ ΠΌΡΡΡΡ ΡΠΎΠ±ΠΎΡΠΈ ΠΉ ΡΠΈ ΠΎΡΡΠΈΠΌΡΡΡ ΡΠ²ΡΠΉ Job Offer! ΠΠΎΡΠΎΠ²ΠΈΠΉ Π΄ΠΎ ΠΏΠ΅ΡΠ΅ΠΌΠΎΠ³?
Π¦ΡΠΊΠ°Π²ΠΎ, ΡΠΎ ΡΠ΅ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ?
- ΠΠ½ΡΡΠΊΠΈΠΉ Π³ΡΠ°ΡΡΠΊ ΡΠΎΠ±ΠΎΡΠΈ β ΡΠΈ ΠΌΠΎΠΆΠ΅Ρ ΡΠ°ΠΌΠΎΡΡΡΠΉΠ½ΠΎ ΠΏΠ»Π°Π½ΡΠ²Π°ΡΠΈ ΡΠ²ΡΠΉ ΡΠΎΠ±ΠΎΡΠΈΠΉ Π΄Π΅Π½Ρ
- ΠΡΠ΄Π΄Π°Π»Π΅Π½Π° ΡΠΎΠ±ΠΎΡΠ° Π°Π±ΠΎ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΠΏΡΠ°ΡΡΠ²Π°ΡΠΈ Π· Π½Π°ΡΠΎΠ³ΠΎ ΠΎΡΡΡΡ Π² ΠΠΈΡΠ²Ρ, ΡΠΎ ΠΏΠΎΠ²Π½ΡΡΡΡ ΠΎΠ±Π»Π°Π΄Π½Π°Π½ΠΈΠΉ Π΄Π»Ρ ΡΠΎΠ±ΠΎΡΠΈ ΠΏΡΠ΄ ΡΠ°Ρ Π²ΡΠ΄ΠΊΠ»ΡΡΠ΅Π½Ρ ΡΠ²ΡΡΠ»Π° + ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΠΊΠΎΡΠΈΡΡΡΠ²Π°ΡΠΈΡΡ ΠΊΠΎΠ²ΠΎΡΠΊΡΠ½Π³ΠΎΠΌ Ρ ΠΠ°ΡΡΠ°Π²Ρ ΡΠ° ΠΎΡΡΡΠΎΠΌ Ρ ΠΡΠ²ΠΎΠ²Ρ.
- 20 ΡΠΎΠ±ΠΎΡΠΈΡ Π΄Π½ΡΠ² Π²ΡΠ΄ΠΏΡΡΡΠΊΠΈ Π½Π° ΡΡΠΊ (ΠΏΡΡΠ»Ρ 3 ΠΌΡΡΡΡΡΠ² ΡΠΏΡΠ²ΠΏΡΠ°ΡΡ) ΡΠ° Π΄ΠΎ 30 Π΄Π½ΡΠ² sick leave Π· ΠΌΠ΅Π΄ΠΈΡΠ½ΠΈΠΌ ΠΏΡΠ΄ΡΠ²Π΅ΡΠ΄ΠΆΠ΅Π½Π½ΡΠΌ. Π ΡΠ°ΠΊΠΎΠΆ ΠΌΠΎΠΆΠ»ΠΈΠ²ΡΡΡΡ ΡΡΠ°Π½ΡΡΠ΅ΡΡ ΡΠΎΠ±ΠΎΡΠΈΡ Π΄Π½ΡΠ² ΡΠ° days off ΠΏΠΎ Π΄Π΅ΡΠΆΠ°Π²Π½ΠΈΡ ΡΠ²ΡΡΠ°Ρ Π£ΠΊΡΠ°ΡΠ½ΠΈ.
- Π ΡΠ·Π½ΠΎΠΌΠ°Π½ΡΡΠ½Ρ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΡ Π΄Π»Ρ Π½Π°Π²ΡΠ°Π½Π½Ρ: Π΄ΠΎΠΏΠΎΠ²ΡΠ΄Ρ ΡΠΏΡΠΊΠ΅ΡΡΠ² Ρ ΡΡΠ·Π½ΠΎΠΌΠ°Π½ΡΡΠ½ΠΈΡ Π½Π°ΠΏΡΡΠΌΠ°Ρ , Π²Π΅Π»ΠΈΠΊΠ° ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Π° Π±ΡΠ±Π»ΡΠΎΡΠ΅ΠΊΠ°, ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ Π·ΠΎΠ²Π½ΡΡΠ½ΡΡ ΠΊΡΡΡΡΠ² Ρ, Π·Π²ΠΈΡΠ°ΠΉΠ½ΠΎ, ΡΡΠΎΠΊΠΈ Π°Π½Π³Π»ΡΠΉΡΡΠΊΠΎΡ ΠΌΠΎΠ²ΠΈ + speaking clubs.
- ΠΠ΅ΡΠ΅Π»Ρ ΡΡΠΌΠ±ΡΠ»Π΄ΡΠ½Π³ΠΈ ΡΠ° ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Ρ ΠΏΠΎΠ΄ΠΎΡΠΎΠΆΡ.
- ΠΡΠΎΠ³ΡΠ°ΠΌΠ° HoneyFit β ΠΊΠΎΠΌΠΏΠ΅Π½ΡΠ°ΡΡΡ ΡΠΏΠΎΡΡΠΈΠ²Π½ΠΈΡ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠ΅ΠΉ ΡΠ° ΡΠ²Π΅Π½ΡΡΠ², ΠΎΡΡΠ»Π°ΠΉΠ½/ΠΎΠ½Π»Π°ΠΉΠ½ ΡΡΠ΅Π½ΡΠ²Π°Π½Ρ ΡΠΎΡΠΎ (ΠΏΠΎ Π·Π°Π²Π΅ΡΡΠ΅Π½Π½Ρ Π²ΠΈΠΏΡΠΎΠ±ΡΠ²Π°Π»ΡΠ½ΠΎΠ³ΠΎ ΡΠ΅ΡΠΌΡΠ½Ρ).
- ΠΠΎΠΏΠΎΠΌΠΎΠ³Π° Π² ΡΠ΅Π»ΠΎΠΊΠ°ΡΡΡ, ΠΎΠΏΠ»Π°ΡΠ° ΠΊΠΎΠ²ΠΎΡΠΊΡΠ½Π³ΡΠ² Π°Π±ΠΎ Π΄ΠΎΠΏΠΎΠΌΠΎΠ³Π° Ρ ΠΏΡΠΈΠ΄Π±Π°Π½Π½Ρ Π·Π°ΡΡΠ΄Π½ΠΈΡ ΡΡΠ°Π½ΡΡΠΉ Π΄Π»Ρ ΠΊΠΎΠΌΡΠΎΡΡΠ½ΠΎΡ ΡΠΎΠ±ΠΎΡΠΈ ΠΏΡΠ΄ ΡΠ°Ρ Π²ΡΠ΄ΠΊΠ»ΡΡΠ΅Π½Π½Ρ Π΅Π»Π΅ΠΊΡΡΠΎΠΏΠΎΡΡΠ°ΡΠ°Π½Π½Ρ (ΠΏΡΡΠ»Ρ 3Ρ ΠΌΡΡΡΡΡΠ² ΡΠΏΡΠ²ΠΏΡΠ°ΡΡ).
- ΠΠ½ΡΡΡΡΡΠ½Ρ ΠΊΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Π° Π²Π°Π»ΡΡΠ° Boosta coins.
- ΠΠ»Π΅ Π½Π°ΠΉΠ³ΠΎΠ»ΠΎΠ²Π½ΡΡΠ΅: Honeytech β ΡΠ΅ ΠΊΠΎΠΌΠ°Π½Π΄Π° ΠΏΡΠΎΡΠ΅ΡΡΠΎΠ½Π°Π»ΡΠ², Π΄Π΅ ΠΊΠΎΠΆΠ½ΠΈΠΉ Π²ΡΠ΄ΡΡΠ²Π°Ρ ΠΏΡΠ΄ΡΡΠΈΠΌΠΊΡ ΡΠ° Π΄ΠΎΡΡΠ³Π°Ρ ΡΠ²ΠΎΡΡ ΡΡΠ»Π΅ΠΉ!
Π§Π΅ΠΊΠ°ΡΠΌΠΎ ΡΠ΅Π±Π΅ Π² ΠΊΠΎΠΌΠ°Π½Π΄Ρ, Π΄Π΅ ΠΊΠΎΠΆΠ΅Π½ Π·Π²ΡΡ ΠΌΠ°Ρ ΡΠ΅Π½Ρ, ΠΊΠΎΠΆΠ½Π° ΡΠΈΡΡΠ° β ΡΡΠ»Ρ, Π° ΠΊΠΎΠΆΠ΅Π½ Π°Π½Π°Π»ΡΡΠΈΠΊ β Π·ΡΡΠΊΠ°. ΠΠ°Π΄ΡΠΈΠ»Π°ΠΉ ΡΠ²ΠΎΡ CV!
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ΠΡΠ·Π½Π΅Ρ Π°Π½Π°Π»ΡΡΠΈΠΊ (Laravel)-E-COMMERCE
Full Remote Β· Ukraine Β· Product Β· 2 years of experience Β· A2 - ElementaryΠΡΠΈΠ²ΡΡ! ΠΠΈ β Π³ΡΡΠΏΠ° ΠΊΠΎΠΌΠΏΠ°Π½ΡΠΉ Β«Π‘ΡΠ·ΡΡ'ΡΒ» β Π½Π°ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΠΉ ΠΏΠΎΡΡΠ°ΡΠ°Π»ΡΠ½ΠΈΠΊ Ρ Π²ΠΈΡΠΎΠ±Π½ΠΈΠΊ Π·ΠΎΠΎΡΠΎΠ²Π°ΡΡΠ² Π· 30-ΡΠΈ ΡΡΡΠ½ΠΎΡ ΡΡΡΠΎΡΡΡΡ ΡΡΠΏΡΡ Ρ. ΠΠ°ΡΡ ΠΏΠ»Π°Π½ΠΈ Π· ΡΠΎΠ·Π²ΠΈΡΠΊΡ Π½Π΅ Π·Π½Π°ΡΡΡ ΠΌΠ΅ΠΆ. ΠΡΡΠ»ΡΠ½ΡΡΡΡ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ ΠΌΠ°Ρ Π½Π°ΡΡΡΠΏΠ½Ρ Π±ΡΠ·Π½Π΅Ρ Π½Π°ΠΏΡΡΠΌΠΊΠΈ: Π΄ΠΈΡΡΡΠΈΠ±ΡΡΡΡ suziria.ua; Π²ΠΈΡΠΎΠ±Π½ΠΈΡΡΠ²ΠΎ ΡΠΎΠ²Π°ΡΡΠ² Π΄Π»Ρ...ΠΡΠΈΠ²ΡΡ! ΠΠΈ β Π³ΡΡΠΏΠ° ΠΊΠΎΠΌΠΏΠ°Π½ΡΠΉ Β«Π‘ΡΠ·ΡΡ'ΡΒ» β Π½Π°ΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΠΉ ΠΏΠΎΡΡΠ°ΡΠ°Π»ΡΠ½ΠΈΠΊ Ρ Π²ΠΈΡΠΎΠ±Π½ΠΈΠΊ Π·ΠΎΠΎΡΠΎΠ²Π°ΡΡΠ² Π· 30-ΡΠΈ ΡΡΡΠ½ΠΎΡ ΡΡΡΠΎΡΡΡΡ ΡΡΠΏΡΡ Ρ. ΠΠ°ΡΡ ΠΏΠ»Π°Π½ΠΈ Π· ΡΠΎΠ·Π²ΠΈΡΠΊΡ Π½Π΅ Π·Π½Π°ΡΡΡ ΠΌΠ΅ΠΆ.
ΠΡΡΠ»ΡΠ½ΡΡΡΡ ΠΊΠΎΠΌΠΏΠ°Π½ΡΡ ΠΌΠ°Ρ Π½Π°ΡΡΡΠΏΠ½Ρ Π±ΡΠ·Π½Π΅Ρ Π½Π°ΠΏΡΡΠΌΠΊΠΈ:
- Π΄ΠΈΡΡΡΠΈΠ±ΡΡΡΡ suziria.ua;
- Π²ΠΈΡΠΎΠ±Π½ΠΈΡΡΠ²ΠΎ ΡΠΎΠ²Π°ΡΡΠ² Π΄Π»Ρ ΡΠ²Π°ΡΠΈΠ½;
- Π²Π»Π°ΡΠ½ΠΈΠΉ ΡΡΡΠ΅ΠΉΠ» masterzoo.ua;
- Π΅ΠΊΡΠΏΠΎΡΡ export.suziria.ua.
ΠΠ΅ΡΠ΅ΠΆΠ° MasterZoo Π½Π°Π»ΡΡΡΡ ΠΏΠΎΠ½Π°Π΄ 200 ΠΌΠ°Π³Π°Π·ΠΈΠ½ΡΠ² ΠΏΠΎ Π²ΡΡΠΉ Π£ΠΊΡΠ°ΡΠ½Ρ. ΠΡΠΎΡΡΠ³ΠΎΠΌ Π±Π°Π³Π°ΡΡΠΎΡ ΡΠΎΠΊΡΠ² ΠΌΠΈ Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°ΡΠΌΠΎ Π·ΡΠΎΠ±ΠΈΡΠΈ ΠΆΠΈΡΡΡ Π΄ΠΎΠΌΠ°ΡΠ½ΡΡ Π²ΠΈΡ ΠΎΠ²Π°Π½ΡΡΠ² ΠΊΠΎΠΌΡΠΎΡΡΠ½ΠΈΠΌ! ΠΠΈ ΠΏΡΠ°Π³Π½Π΅ΠΌΠΎ Π±ΡΡΠΈ Π½Π°ΠΉΠΊΡΠ°ΡΠΎΡ ΠΌΠ΅ΡΠ΅ΠΆΠ΅Ρ Π·ΠΎΠΎ-ΠΌΠ°ΡΠΊΠ΅ΡΡΠ² Π² Π£ΠΊΡΠ°ΡΠ½Ρ, ΡΠΊΠ° Π²Π°ΡΡΠ° Π½Π°ΠΉΠ²ΠΈΡΠΎΡ Π΄ΠΎΠ²ΡΡΠΈ ΡΠ²ΠΎΡΡ ΠΊΠ»ΡΡΠ½ΡΡΠ².
ΠΠ»Ρ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ e-commerce ΡΠ°ΠΉΡΡ ΡΠ° ΠΌΠΎΠ±ΡΠ»ΡΠ½ΠΎΠ³ΠΎ Π΄ΠΎΠ΄Π°ΡΠΊΡ ΠΌΠ΅ΡΠ΅ΠΆΡ MasterZoo, Ρ Π·Π²'ΡΠ·ΠΊΡ Π· ΡΠΎΠ·ΡΠΈΡΠ΅Π½Π½ΡΠΌ ΡΡΠ°ΡΡ ΠΊΠΎΠΌΠ°Π½Π΄Π° Π² ΠΏΠΎΡΡΠΊΡ Π±ΡΠ·Π½Π΅Ρ-Π°Π½Π°Π»ΡΡΠΈΠΊΠ° ΠΊΠΎΠΌΠ°Π½Π΄ΠΈ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ.
Π©ΠΎ ΡΡΠ΅Π±Π° ΡΠΎΠ±ΠΈΡΠΈ:
- ΠΠ±ΡΡ ΡΠ° Π°Π½Π°Π»ΡΠ· Π±ΡΠ·Π½Π΅Ρ-Π²ΠΈΠΌΠΎΠ³;
ΠΠΈΠ·Π½Π°ΡΠ΅Π½Π½Ρ ΠΏΠΎΡΡΠ΅Π± Π±ΡΠ·Π½Π΅ΡΡ ΡΠ° ΠΊΠ»ΡΡΠΎΠ²ΠΈΡ Π·Π°ΡΡΠΊΠ°Π²Π»Π΅Π½ΠΈΡ ΡΡΠΎΡΡΠ½;
- ΠΠ½Π°Π»ΡΠ· ΡΡΠ½ΡΡΡΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠ² Ρ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠ° BPMN-Π΄ΡΠ°Π³ΡΠ°ΠΌ Π΄Π»Ρ ΡΡ Π²ΡΠ·ΡΠ°Π»ΡΠ·Π°ΡΡΡ;
- Π ΠΎΠ·ΡΠΎΠ±ΠΊΠ° ΡΠ΅Ρ Π½ΡΡΠ½ΠΎΡ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΡΡ;
- Π€ΠΎΡΠΌΡΠ²Π°Π½Π½Ρ Π²ΠΈΠΌΠΎΠ³ Π΄ΠΎ ΡΠΈΡΡΠ΅ΠΌΠΈ ΡΠ° ΠΎΠΏΠΈΡ Π±ΡΠ·Π½Π΅Ρ-ΠΏΡΠΎΡΠ΅ΡΡΠ²;
- Π‘ΡΠ²ΠΎΡΠ΅Π½Π½Ρ UML-Π΄ΡΠ°Π³ΡΠ°ΠΌ (Use Case, Activity, Sequence) Π΄Π»Ρ ΡΠ΅Ρ Π½ΡΡΠ½ΠΎΡ Π΄Π΅ΡΠ°Π»ΡΠ·Π°ΡΡΡ;
- ΠΠ½Π°Π»ΡΠ· Π΄Π°Π½ΠΈΡ ΡΠ° ΡΠΈΠ½ΠΊΡ;
- ΠΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ ΡΠ΅Π½Π΄Π΅Π½ΡΡΠΉ ΡΠΈΠ½ΠΊΡ ΡΠ° ΠΏΠΎΠ²Π΅Π΄ΡΠ½ΠΊΠΈ ΠΊΠΎΡΠΈΡΡΡΠ²Π°ΡΡΠ²;
- ΠΡΡΠ½ΠΊΠ° Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΠΎΡΠΎΡΠ½ΠΈΡ ΡΡΡΠ΅Π½Ρ Ρ Π²ΠΈΡΠ²Π»Π΅Π½Π½Ρ Π·ΠΎΠ½ Π΄Π»Ρ ΠΏΠΎΠΊΡΠ°ΡΠ΅Π½Π½Ρ;
- Π£ΡΠ°ΡΡΡ Ρ Π²ΠΏΡΠΎΠ²Π°Π΄ΠΆΠ΅Π½Π½Ρ Π·ΠΌΡΠ½;
- ΠΠΎΠΎΡΠ΄ΠΈΠ½Π°ΡΡΡ ΡΠΎΠ·ΡΠΎΠ±ΠΊΠΈ ΡΠ° ΡΠ½ΡΠ΅Π³ΡΠ°ΡΡΡ Π½ΠΎΠ²ΠΈΡ ΡΡΠ½ΠΊΡΡΠΎΠ½Π°Π»ΡΠ½ΠΈΡ ΠΌΠΎΠΆΠ»ΠΈΠ²ΠΎΡΡΠ΅ΠΉ;
- ΠΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ BPMN-Π΄ΡΠ°Π³ΡΠ°ΠΌ Π΄Π»Ρ ΠΎΠΏΠΈΡΡ Π·ΠΌΡΠ½ Ρ ΠΏΡΠΎΡΠ΅ΡΠ°Ρ ;
ΠΠΎΠ½ΡΡΠΎΡΠΈΠ½Π³ Ρ ΠΏΠΎΠΊΡΠ°ΡΠ΅Π½Π½Ρ ΠΏΡΠΎΡΠ΅ΡΡΠ²;
- ΠΠ½Π°Π»ΡΠ· ΠΊΠ»ΡΡΠΎΠ²ΠΈΡ ΠΏΠΎΠΊΠ°Π·Π½ΠΈΠΊΡΠ² Π΅ΡΠ΅ΠΊΡΠΈΠ²Π½ΠΎΡΡΡ;
- ΠΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ UML-Π΄ΡΠ°Π³ΡΠ°ΠΌ Π΄Π»Ρ ΠΌΠΎΠ΄Π΅Π»ΡΠ²Π°Π½Π½Ρ Π½ΠΎΠ²ΠΈΡ ΠΏΡΠΎΡΠ΅ΡΡΠ² ΡΠ° Π°ΡΡ ΡΡΠ΅ΠΊΡΡΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠΈ.
ΠΠΈ ΠΏΡΠΎΠΏΠΎΠ½ΡΡΠΌΠΎ:
- ΠΠΈΠ½Π°Π³ΠΎΡΠΎΠ΄Ρ Π²ΡΠ΄ΠΏΠΎΠ²ΡΠ΄Π½ΠΎ ΡΠΈΠ½ΠΊΡ;
- Π£ΡΠ°ΡΡΡ Ρ ΠΏΡΠΎΠ΅ΠΊΡΠ°Ρ , ΡΠΊΡ ΠΏΡΠ΄Π²ΠΈΡΠ°ΡΡ ΡΠ²ΠΎΡ Π΅ΠΊΡΠΏΠ΅ΡΡΠ½ΡΡΡΡ Π΄ΠΎ Π½Π΅Π±Π΅Ρ;
- ΠΡΡΡΡ ΠΠ’ ΠΊΠΎΠΌΠ°Π½Π΄Ρ, ΡΠΊΠ° ΠΏΡΠ΄ΡΡΠΈΠΌΡΡ ΡΠ° Π΄ΠΎΠΏΠΎΠΌΠ°Π³Π°Ρ;
- ΠΠΎΡΠΏΠΎΡΠ°ΡΠΈΠ²Π½Ρ Π·Π½ΠΈΠΆΠΊΡ Π½Π° ΠΏΡΠΎΠ΄ΡΠΊΡΡΡ Π΄Π»Ρ ΡΠ²ΠΎΠ³ΠΎ Π΄ΠΎΠΌΠ°ΡΠ½ΡΠΎΠ³ΠΎ Π²ΠΈΡ ΠΎΠ²Π°Π½ΡΡ;
- ΠΡΠ΄Π΄Π°Π»Π΅Π½Ρ ΡΠΎΠ±ΠΎΡΡ Π°Π±ΠΎ Π³ΡΠ±ΡΠΈΠ΄Π½ΠΈΠΉ ΡΠΎΡΠΌΠ°Ρ ΡΠΎΠ±ΠΎΡΠΈ (ΡΡΡΠ°ΡΠ½ΠΈΠΉ, pets friendly ΠΎΡΡΡ + Π²ΡΠ΄Π΄Π°Π»Π΅Π½ΠΎ).
Π―ΠΊΡΠΎ ΡΠ΅Π±Π΅ Π·Π°ΡΡΠΊΠ°Π²ΠΈΠ»Π° Π²Π°ΠΊΠ°Π½ΡΡΡ, Π²ΡΠ΄ΠΏΡΠ°Π²Π»ΡΠΉ ΡΠ²ΠΎΡ ΡΠ΅Π·ΡΠΌΠ΅!
ΠΡΠ΄Π΅ΠΌΠΎ ΡΠ°Π΄Ρ Π±Π°ΡΠΈΡΠΈ ΡΠ΅Π±Π΅ Π² Π½Π°ΡΡΠΉ ΠΊΠΎΠΌΠ°Π½Π΄Ρ!
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