VeraData

We build internal products and automation for our own teams to improve day-to-day business processes. Most tasks revolve around processing large datasets (millions of rows) and turning them into reliable, reusable outputs.

You'll work 50/50 between Python development and data work: building scripts/services and data pipelines, mainly with Pandas, plus some SQL and PySpark.

    What You'll Do

• Build internal tools and automation around data processing and reporting.
• Develop and maintain pipelines that ingest data from APIs and large files.
• Transform and validate data using Pandas; write clean, tested, maintainable Python.
• Use SQL mainly to extract data and for joins/aggregations when needed.
• Contribute to large-scale processing (PySpark/Spark) when applicable.

• Refactor and optimize existing scripts and pipelines; improve performance, readability, and reliability (tests/logging).

   

    What We're Looking For

• 2+ years of experience with Python in production.
• Strong Pandas: efficient transformations, joins/merges, memory/performance considerations.
• Solid engineering habits: tests, code review, debugging, and readable code.
• Working knowledge of SQL (MS SQL Server is our primary DB, but any RDBMS is fine).
• Comfortable with Linux and Git; daily tooling skills (e.g., VS Code).
• Excellent organizational and task management abilities.
• Self-motivated with the ability to work independently.
• Good written and spoken English communication skills.

    Nice to Have

• PySpark/Spark and/or Hadoop exposure; distributed processing concepts.
• Azure experience (storage/compute) or participation in on-prem → cloud initiatives; workflow orchestration is a plus.
• Data modeling fundamentals and basic ML understanding; а portfolio (GitHub/website) or examples of end-to-end projects/products (clean repo structure, README, tests) is a plus.

      Must-have

• Strong JavaScript (ES6+) and TypeScript knowledge. Solid practical experience with React: components, hooks, state/props, lifting state.
• Experience with state management libraries (preferably Zustand, Redux Toolkit, or React Query).
• Ability to work with UI component libraries and styling tools (Shadcn, Tailwind CSS).
• Data table libraries experience (Material React Table / TanStack Table or alternatives).
• Experience working with REST APIs: fetching, optimistic updates, error handling.
• Ability to independently implement backend logic (Node.js + Express/Fastify/NestJS or similar) for new endpoints or business logic.
• Understanding of server-side concepts: routing, validation, auth basics, working with databases (SQL/NoSQL) at a basic level.
• Good analytical and mathematical reasoning (many features require non-trivial data transformations).
• HTML5/CSS3 knowledge including responsive layouts (Flexbox/Grid) and cross-browser aspects.
• Familiarity with code quality tools (ESLint, Prettier) + DRY/KISS principles.
• Git/GitHub workflow: branches, PRs, resolving feedback.
• English sufficient for documentation and task discussion.
   

     Nice to have

• Testing experience (Jest + React Testing Library).
• Performance awareness (React rendering, memoization, profiling).
• Familiarity with CI/CD (GitHub Actions).
• Basic understanding of backend architecture (monolith/microservices).
   

     Main responsibilities

• Rewrite parts of an existing React-based application into a standalone application using React + TypeScript.
• Build and maintain React components with clean, modular, and reusable structure.
• Implement data-intensive logic and transformations with attention to mathematical correctness.
• Integrate REST APIs and extend backend functionality when needed (Node.js + DB).
• Maintain consistent code style (ESLint/Prettier) and add tests for core logic.
• Fix bugs, refactor legacy code, and improve maintainability under lead/mentor guidance.
• Ensure performance, responsive UI, and baseline accessibility.
• Participate in technical discussions and collaborate closely with other developers.

We are looking for a Data Engineer to join our team!

Data Engineer is responsible for designing, maintaining, and optimizing data infrastructure for data collection, management, transformation, and access.

He/she will be in charge of creating pipelines that convert raw data into usable formats for data scientists and other data consumers to utilize.

Data Engineer should be comfortable working with RDBMS and has a good knowledge of the appropriate RDBMS programming language(s) as well.

The Data Engineer fulfills processing of client data based on proper specification and documentation.

     Main responsibilities:

• Design and develop ETL pipelines;
• Data integration and cleansing;
• Implement stored procedures and function for data transformations;
• ETL processes performance optimization.

     Skills and Requirements:

• Experience with ETL tools (to take charge of the ETL processes and performs tasks connected with data analytics, data science, business intelligence and system architecture skills);
• Database/DBA/Architect background (understanding of data storage requirements and design warehouse architecture, should have the basic expertise with SQL/NoSQL databases and data mapping, the awareness of Hadoop environment);
• Data analysis expertise (data modeling, mapping, and formatting, data analysis basic expertise is required);
• Knowledge of scripting languages (Python is preferable);
• Troubleshooting skills (data processing systems operate with large amounts of data and include multiple structural elements. Data Engineer is responsible for the proper functioning of the system, which requires strong analytical thinking and troubleshooting skills);
• Tableau experience is good to have;
• Software engineering background is good to have;
• Good organizational skills, and task management abilities;
• Effective self-motivator;
• Good communication skills in written and spoken English.

     Salary Range

Compensation packages are based on several factors including but not limited to: skill set, depth of experience, certifications, and specific work location.

We’re building an intelligent AI agent that doesn’t just answer questions, but reasons, retrieves, understands context, and acts across documents, SQL data, and visual inputs.

If you're excited by rapid experimentation, real users, and pushing LLMs beyond chat - this role is for you.

     What You'll Do

• Design and implement an intelligent chatbot/agent capable of reasoning over documents, structured SQL data, and multimodal inputs
• Fine-tune or integrate LLMs (OpenAI, Ollama, Deepseek, etc.) for contextual Q&A
• Develop text analytics pipelines (sentiment analysis, classification, topic modeling)
• Design image processing systems for tagging, feature extraction
• Experiment rapidly with new ideas, validate hypotheses
• Support and work with Hadoop clusters for big data processing.
  
  What We're Looking For
• 2+ years of experience as ML/AI engineering or in a similar role
• Bachelor’s degree in Computer Science, or a related field
• Strong proficiency in Python, and solid experience with ML frameworks
• Deep understanding of NLP and CV fundamentals
• Hands-on experience with AI/ML projects deployed in production
• Experience integrating LLMs, retrieval pipelines in multi-step reasoning agents
• Practical experience in text/image processing
  
  Nice to Have
• Knowledge of OCR, captioning
• Experience with prompt engineering
• Experience in predictive modeling