Data Engineer

We are looking for an experienced Data Engineer to design and maintain robust data infrastructure across our systems. In this role, you will be responsible for building scalable data pipelines, ensuring data integrity, and integrating third-party data sources. Your primary focus will be to enable efficient data flow and support analytical capabilities across the organization. You will also contribute to the development of our data architecture, implement best engineering practices, and collaborate closely with cross-functional teams to turn raw data into actionable insights.

Responsibilities

• Communicate with technical and non-technical stakeholders to gather and clarify business requirements
• Review and analyze data and business logic to ensure consistency, accuracy, and reliability
• Design, implement, and maintain data pipelines for efficient and scalable data processing
• Integrate, maintain, and support data solutions and third-party data sources
• Research and evaluate third-party tools, services, and components for potential use
• Follow engineering best practices, including code reviews, testing, refactoring, and continuous delivery
• Design, optimize, and maintain data storage solutions

Requirements

• 3+ years of commercial experience in Data Engineering
• Experience gathering business requirements and communicating with stakeholders
• Strong knowledge of Data Warehouse (DWH) architecture and principles
• Hands-on experience designing data warehouses and building ETL pipelines
• Deep practical experience with Python
• Hands-on experience in one or more of the following areas: data processing using PySpark, Apache Spark, Pandas, or similar frameworks; data scraping; integration of third-party data sources and APIs
• Proficiency in SQL and relational databases such as PostgreSQL and MySQL
• Hands-on experience with column-oriented databases such ClickHouse, Snowflake, Cassandra, BigQuery (many tables with millions of records and above each)
• Solid understanding of software design patterns, algorithms, and data structures
• Intermediate English proficiency

Will be a plus

• Experience with messaging platforms such as RabbitMQ or Kafka
• Familiarity with DataOps practices and data pipeline automation
• Familiarity with CI/CD pipelines and Kubernetes environments
• Background in FinTech or Trading domains

We offer

• Tax expenses coverage for private entrepreneurs in Ukraine
• Expert support and guidance for Ukrainian private entrepreneurs
• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays as per the company's approved Public holiday list
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear and related expenses)

Role mission

Use data science approach to analyse and enhance company performance

Requirements hard skills

— 4+ years data science experience
— 2+ years of team management experience
— Master’s degree or higher in Computer Science/Mathematics/Physics/Electric engineering or equivalent
— Strong experience in software engineering in Python
— Ability to build applications and familiarity with best practices such as CI/CD, testing, and coding standards
— Experience in machine learning platforms, frameworks, and libraries
— Deep understanding of classic models like linear regression, logistic regression, or gradient boosting decision trees
— Good understanding of mathematical statistics and probability theory
— Strong knowledge of SQL, including complex queries and analytic functions
— Experience with cloud platforms
— Research mindset and math-oriented intelligence
— Have a problem-solving mindset and focused on obtaining the result
— English level — Intermediate+

Requirements soft skills

Customer first
Trust
Passionate about work
Continuous learning
Result driven
Ownership

Responsibilities

- Review and understand the data, including checking logic and cleaning outliers as needed;
- Carry out feature engineering, using different techniques of feature preparation, transformation, normalization, or generation;
- Conduct model training and evaluation, developing pipelines for model training and experimenting;
- Be responsible for model monitoring and maintenance;
- Work alongside engineers, and product teams to help develop a core suite of data products and services;
- Communicate with both technical and non-technical audiences to gather requirements and present findings;
- Engage with research and business stakeholders and help drive AI/ML strategies and identify areas where business problems that can be solved in creative ways utilizing data and the power of algorithms;
- Oversee operational support and maintenance of products and services delivered by the AI/ML team;
- Develop team members.