DataArt

Client

Our client is an international SaaS company developing tools that empower businesses to create highly engaging digital experiences. Their solutions are trusted by thousands of organizations worldwide to collect, analyze, and act on user data effectively.

Project overview

The project is an interactive form builder designed for marketers, researchers, HR, sales, and customer experience teams to create engaging, conversational online forms, surveys, and quizzes.

Key features:
Visually appealing conversational design optimized for high completion rates
AI-powered data interpretation
Workflow and logic builders for personalized experiences
Brand customization options
Seamless integrations with various tools to automate data collection and streamline workflows

Position overview

We are seeking a Full Stack Engineer who builds with AI in the loop — both as a daily development practice and as a product capability. You are fluent with coding agents (Claude Code, Cursor, Copilot) and ship faster because of them, not despite them. You understand how to design, prompt, evaluate, and operate LLM-backed features in production — including model selection, context engineering, evals, guardrails, and cost and latency tradeoffs.

Beyond AI, you have deep Golang and React/TypeScript expertise and own features end-to-end: from understanding business requirements, through writing and testing code, to deployment and production monitoring. This role requires strong autonomy, proactive communication, and the ability to deliver reliable, scalable solutions in a modern cloud environment.

This position operates according to the CET time zone.

Responsibilities

• Design and ship LLM-powered product features: prompt design, retrieval, tool and function calling, structured outputs, streaming, evaluation harnesses, and guardrails.
• Operate AI features in production: monitor quality, latency, cost, and failure modes; iterate on prompts, models, and architectures based on real usage.
• Use AI coding tools (Claude Code, Cursor, Copilot) as a core part of your workflow to accelerate delivery without compromising code quality.
• Design, develop, and maintain backend services using Golang and frontend applications using React/TypeScript.
• Collaborate with product managers, designers, and other engineers to translate business requirements into technical solutions.
• Implement event-driven architectures leveraging Kafka for real-time data processing.
• Manage and optimize AWS environments, ensuring scalability and reliability.
• Define and maintain infrastructure using Terraform and deploy services in Kubernetes clusters.
• Build and maintain CI/CD pipelines in Jenkins for automated deployments.
• Ensure high-quality code through comprehensive testing and code reviews.
• Monitor application performance and troubleshoot issues in production environments.
• Contribute to UI/UX improvements and ensure seamless integration between frontend and backend.

Requirements

• Demonstrable production experience shipping LLM-powered features. Be ready to walk through a feature you built: prompts, evaluation approach, failure modes you fixed, and how you measured success.
• Hands-on with at least one major LLM provider's API (Anthropic, OpenAI, AWS Bedrock, or equivalent), including streaming, tool use, and structured outputs.
• Daily use of AI coding assistants in your workflow; able to articulate where they help, where they hurt, and how you maintain code quality.
• Strong, in-depth knowledge of Golang.
• Experience delivering complex backend systems from design to production.
• Solid background with Kafka and event-driven architectures.
• Hands-on experience managing AWS environments.
• Proficiency with Terraform for infrastructure-as-code.
• Experience deploying and operating services in Kubernetes.
• Building CI/CD pipelines in Jenkins.
• Proven ability to ensure quality through comprehensive testing.
• Strong proficiency in React and TypeScript.
• Experience contributing to front-end features, UI components, and client-side logic.
• Ability to seamlessly integrate frontend with backend services.
• Excellent English communication skills, written and spoken.
• Self-driven and able to work independently while managing workload effectively.

Nice to have

• Experience with agent frameworks, multi-step tool-use loops, or RAG systems at scale.
• Built or maintained an evaluation pipeline (offline evals, LLM-as-judge, human review loops).
• Open-source contributions, published writing, or talks on applied AI engineering.

Client

Our client is a leading US-based company providing environmental services such as customized waste and recycling programs, and innovative sustainability solutions.

Project overview

The project focuses on migrating enterprise databases from Oracle on-premises infrastructure to Azure MS SQL. The successful candidate will help establish robust testing processes, build automated validation solutions, and ensure data accuracy, integrity, and consistency throughout the migration journey.

Position overview

We are looking for a Senior Data QA Engineer with strong expertise in Python-based test automation and advanced SQL to join a large-scale database migration initiative. In this role, you will be responsible for defining and implementing the overall testing strategy, establishing automation frameworks, validating data quality, and ensuring a smooth migration from Oracle on-premises environments to Azure MS SQL.

Responsibilities

• Design, implement, and maintain a scalable test automation framework using Python.
• Define and establish database migration testing processes, standards, and best practices.
• Develop and execute test cases for migration validation, data reconciliation, and quality assurance.
• Validate data accuracy, integrity, completeness, and consistency during migration from Oracle to Azure MS SQL.
• Analyze test results and provide clear reporting on defects, risks, and overall migration quality.
• Collaborate with engineering, database, and project teams to ensure quality throughout the migration lifecycle.
• Identify, investigate, and resolve data discrepancies and migration-related issues.
• Drive continuous improvement of testing methodologies, automation capabilities, and QA processes.

Requirements

• Strong experience in Data Quality Assurance, Database Testing, or related QA disciplines.
• Hands-on experience developing test automation solutions using Python.
• Advanced SQL skills with the ability to write and optimize complex queries.
• Proven experience with database migration testing and validation.
• Strong understanding of Oracle and Microsoft SQL Server environments.
• Experience with data validation, reconciliation, and integrity testing.
• Excellent analytical, troubleshooting, and problem-solving skills.
• Ability to work independently, take ownership, and drive testing activities end-to-end.
• Strong communication and collaboration skills.

Nice to have

• Experience working with Azure cloud environments.
• Knowledge of Azure SQL and related data services.
• Experience supporting large-scale enterprise migration or modernization programs.
• Familiarity with data warehousing, ETL processes, and data transformation validation.
• Experience implementing test automation frameworks for data-intensive applications.

Project overview

This project focuses on building and enhancing an enterprise data warehouse platform that supports data driven decision making across complex business domains. The work involves designing scalable data models, ingestion pipelines, and transformation logic to ensure high quality and consistent data.

Team

You will be part of a collaborative data team working alongside data designers, data engineers, and platform specialists. The team operates in an agile environment, shares knowledge actively, and follows established data design standards and review practices.

Position overview

We are looking for a Senior Data Designer who can operate as the bridge between business stakeholders and engineering — someone equally comfortable running a requirements workshop and designing a Kimball-style dimensional model. This is not a pure modelling role: you'll investigate source systems, challenge and shape business requirements before any design work starts, and turn that understanding into governed, well-documented data platform designs that engineering teams can implement. You will contribute to data ingestion design, transformation logic, and data harmonization while working closely with stakeholders and platform teams.

Technology stack

Core: SQL, dimensional/Kimball data modelling, enterprise data warehouse tools, cloud data platforms
Additional technologies used within the project: Python, PySpark, data profiling tooling

Responsibilities

• Design and document Enterprise Data Warehouse objects: data models, source-to-target mappings, model diagrams, and supporting design documentation that engineers deliver from
• Work with stakeholders and source-system SMEs to onboard new data sources and adapt designs to what each source provides
• Clarify the intent behind requirements before designing: why the stakeholder needs it and whether existing structures already cover it
• Profile and analyze source data to validate design assumptions
• Define data quality rules as part of designs for downstream teams to implement
• Investigate reported data issues, identify root causes, and propose design-level fixes
• Take designs through peer and design review; give and take constructive challenge
• Keep stakeholders informed: raise issues early, ask instead of assuming, follow up until unblocked

Requirements

• Strong practical foundations of dimensional modeling — able to design warehouse models from raw source data and explain the reasoning behind design choices
• Hands-on experience producing source-to-target mapping documentation
• Working understanding of data platform layering and data load approaches
• Confident SQL for data profiling and validation
• Strong written and spoken English; comfortable gathering requirements and managing stakeholder expectations
• Attention to detail; comfortable working in a governed environment with reviews and design standards, and data privacy/PII classification requirements

Nice to have

• SAP as a source system
• Retail domain experience
• Agile delivery experience

Project overview

You will be involved in a large scale enterprise Salesforce implementation focused on improving customer relationship management processes and operational efficiency. The project supports continuous platform enhancements, user adoption, and data quality improvements across multiple business units.

Position overview

We are looking for a Junior Salesforce Administrator who will support the ongoing development and maintenance of a Salesforce environment within an enterprise project. You will work closely with experienced Salesforce specialists, gaining hands on experience while contributing to real business solutions.

Technology stack

Salesforce Lightning Experience, Salesforce CRM, Reports and Dashboards, Data Loader, Microsoft Excel, Agile tools, basic data management tools

Responsibilities

• Support daily Salesforce administration tasks within the project environment
• Maintain user accounts, profiles, and permission sets under senior guidance
• Configure standard Salesforce features such as fields, page layouts, and picklists
• Assist in building reports and dashboards to support business needs
• Provide first level user support by logging and investigating issues
• Escalate complex issues to senior team members when required
• Assist with data imports, exports, and data quality activities
• Participate in testing configurations and new features before release
• Document system configurations, processes, and user guides
• Collaborate with team members and stakeholders to support enhancements
• Apply Salesforce best practices and contribute to continuous improvement activities

Requirements

• Basic understanding of Salesforce platform functionality through coursework, training, certification, internship, or personal projects
• Familiarity with Salesforce Lightning Experience
• Understanding of CRM concepts and business processes
• Ability to analyze issues and propose structured solutions
• Strong communication skills in English, both written and spoken
• Ability to work effectively in a collaborative team environment
• Willingness to learn and develop Salesforce administration skills

Nice to have

• Salesforce Administrator Certification ADM 201 or preparation towards certification
• Experience with Microsoft Excel for data handling and analysis
• Exposure to Agile methodologies and delivery practices
• Basic understanding of data management and data quality principles

Client

Our client is a large international manufacturing company listed in the S&P 500, operating a complex, multi-site global environment. As part of a Data Strategy Development initiative, the organization is defining a clear, pragmatic, and scalable data strategy to improve decision-making, reduce manual processes, strengthen data ownership, and establish a strong foundation for future analytics and digital transformation. The engagement focuses on strategy definition and is expected to continue into platform and analytics implementation phases.

Project overview

This initiative focuses on establishing a robust, enterprise-wide data strategy and building a data-driven culture. The project involves standing up a modern target operating model, deploying advanced data platforms, and creating the data leadership architecture necessary to support long-term business capabilities.

Position overview

The Data Consultant will lead the people and process aspects of the organization's data strategy, specifically driving data governance, change management, and the data literacy agenda. Serving as a business-facing leader, this role acts as the primary bridge between business stakeholders, executive sponsors, and the technical delivery teams. The ideal candidate possesses strong business acumen paired with sufficient technical literacy to maintain credibility with data architecture teams and ensure seamless strategic alignment.

Responsibilities

• Data Governance: Lead the implementation of the data governance blueprint, including the operating model, defining roles (data owners and stewards), establishing policies and standards, and facilitating and sustaining governance forums.
• Change Management: Own and execute the comprehensive change management plan, covering stakeholder engagement, communications, user adoption, and the transition to the target operating model.
• Data Leadership: Drive the data leadership and data literacy agenda to foster a mature, data-driven organizational culture and build internal capabilities.
• Stakeholder Partnership: Collaborate directly with business and functional leaders to capture requirements, prioritize data use cases, and secure organizational buy-in.
• Executive Alignment: Maintain alignment across executive sponsors, the Data Architect, and change program leads regarding project scope, priorities, risks, and milestones.
• Technical Alignment: Ensure all governance processes and adoption strategies are technically grounded by maintaining a strong baseline understanding of the deployed data platforms and architecture.
• Artifact Ownership: Author and quality-assure core strategic artifacts, including governance blueprints, operating models, and change plans tailored for executive audiences.

Requirements

• Proven track record of leading data governance and/or data management programs within a complex enterprise environment.
• Strong change management capability, with demonstrated experience in stakeholder engagement, communication strategy, and operating-model transitions.
• Proven ability to effectively engage, collaborate with, and influence senior and C-level stakeholders.
• Sound technical literacy regarding data platforms and analytics, enabling close partnership with architects and engineers.
• Exceptional communication and facilitation skills, with a verified ability to translate complex concepts between business and technical audiences.

Nice to have

• Experience in manufacturing or industrial enterprise environments.
• Background in large-scale data or digital transformation programs.
• Familiarity with Azure, Snowflake, and modern cloud data platforms.
• Experience contributing to executive-level strategy reports and board-level materials.
• Consulting or principal-level advisory experience in global organizations.

Our client is a prominent global wealth and asset management firm focused on delivering innovative investment solutions and a networked ecosystem of international opportunities. The organization operates within a highly regulated environment, prioritizing the transformation of complex concepts into actionable financial strategies for a global clientele.

Project overview

The project involves the development and expansion of a centralized, scalable data ecosystem. Having successfully ingested the initial data source, the team is now moving into a high-growth phase to integrate multiple high-value financial and operational data streams. The goal is to provide C-level executives and advisors with a unified, reliable reporting layer for strategic decision-making.

Position overview

As a Senior Data Engineer, you will be a technical cornerstone of the data platform team. You will be responsible for the end-to-end engineering of data pipelines, from ingestion to transformation, ensuring that the Snowflake warehouse is optimized for complex wealth management analytics. You will work at the intersection of sophisticated financial data and enterprise-grade engineering.

Responsibilities

• Build and maintain scalable data pipelines for ingestion into Snowflake.
• Develop and manage transformations using dbt, including modeling, testing, and comprehensive documentation.
• Design and orchestrate complex data workflows using Prefect.
• Utilize Workato to integrate and normalize data from critical SaaS platforms, including Addepar, NetSuite, Salesforce, Morningstar, and UKG.
• Design specialized data models tailored for portfolio, client, and financial reporting.
• Ensure data quality, lineage, and governance best practices while optimizing performance and costs within Snowflake.
• Partner with Tableau developers and business stakeholders to align technical delivery with reporting needs.

Requirements

• 5+ years of experience in data engineering with a focus on building modern data platforms.
• Hands-on experience with Snowflake and dbt, supported by strong SQL skills and advanced data modeling expertise.
• DBT certification.
• Proven familiarity with ETL/ELT patterns and API-based ingestion.
• Practical experience with orchestration tools such as Prefect or Airflow.
• A solid understanding of financial or wealth management data structures.

Nice to have

• Experience supporting reporting requirements for Tableau-based visualization layers.
• Experience within the Wealth Management or Investment Management sector, with specific familiarity handling investment and portfolio-related data.
• Understanding of regulatory requirements regarding financial data handling and privacy.
• Background in integrating market data providers such as Bloomberg or Morningstar.
• Advanced SQL skills and experience with Python for data engineering tasks.

Client

The company is one of the regional leaders in the industry and is currently launching their new product, an international platform for ticket sales. The company's annual income exceeds 100 million euros.

The client uses various tools to reach their customers, such as a mobile app, a responsive web application, or communicating with them directly through the call center. The system is very complex, it must comply with a large number of regulations. We provide APIs for different clients including the biggest Global Distribution Systems (GDSes).

Our client is committed to ensuring that the system will be as modern as possible. It is based on microservice architecture with the use of continuous integration, where a few hundred components operate independently of each other and can be used as they become available. This increases the modularity of the system and optimizes the use of the services. All components run on AWS.

Team

Several independent teams are working on the project. The goals of each team are limited to the part of the system they're working on. DataArt's specialists are working on the back-end in one of the teams.

Position overview

DataArt is currently helping to modernize and develop the IT system of an independent online retailer of railroad tickets.

Technology stack

.NET (always working with newest versions)
microservices
REST API
MSSQL migrating to Postgres, DynamoDB

Responsibilities

• Refactoring and expanding tickets selling system
• Develop, enhance, and maintain high-quality, scalable code
• Work collaboratively with cross-functional teams to support the implementation of new features and achieve their objectives

Position overview

We're looking for a Senior Windows Drivers Engineer to join our Endpoint team and help build and enhance the core technology behind Cybereason's Windows agent. In this role, you'll design and implement low-level Windows components, including Windows kernel drivers and user-mode services, that power advanced threat detection and response capabilities. You'll work closely with security researchers, sensor developers, and platform engineers to ensure our agent is stable, stealthy, and performant across all supported environments.

This role demands strong C++ expertise, deep knowledge of Windows OS internals, KMDF (Kernel-Mode Driver Framework), and a passion for building secure, high-impact software.

Responsibilities

• Design and develop low-level components for the Windows endpoint sensor, focusing on stability, performance, and stealth.
• Build kernel-mode drivers and user-mode services that collect, filter, and analyze endpoint telemetry.
• Implement robust techniques for process/thread monitoring, registry tracking, file system interception, and network event visibility.
• Debug complex kernel-mode and user-mode issues across multiple Windows versions.
• Collaborate with researchers and product teams to translate threat intelligence into product features.
• Conduct code reviews, mentor engineers, and contribute to architectural decisions.
• Stay current with Windows internals, security trends, and system programming best practices.

Requirements

• 5+ years of hands-on experience in C++ development (C++11 or later).
• In-depth understanding of Windows internals, including kernel architecture, system calls, memory management, and drivers.
• Proven experience developing Windows kernel drivers using KMDF, Windows Filtering Platform (WFP), minifilters, and ETW.
• Strong debugging and reverse engineering skills using tools such as WinDbg, Process Monitor, Process Explorer, IDA, or Ghidra.
• Familiarity with Windows security mechanisms, including integrity levels, UAC, AppLocker, and Secure Boot.
• Experience using Visual Studio, Windows Driver Kit (WDK), and related development environments.

Nice to have

• Experience building or contributing to endpoint security products (EDR, AV, EPP, etc.).
• Familiarity with Windows telemetry, Event Logs, Sysmon, and ETW tracing.
• Experience with malware analysis, Windows exploitation techniques, or SOC/DFIR workflows.
• Experience in the cybersecurity domain is a plus.
• Scripting skills in PowerShell or Python for automation and testing.
• Understanding of kernel-mode security evasion techniques and defensive mechanisms.
• Experience with code signing, driver deployment, and secure update mechanisms.
• Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience.