Jobs Kharkiv, Data Engineer

Client

Our client is a large international manufacturing company listed in the S&P 500 and operating within a complex, multi‑site global environment. As part of a Data Strategy Development initiative, the organization is working to define a clear, pragmatic, and scalable data strategy aimed at improving decision‑making, reducing manual processes, strengthening data ownership, and laying a solid foundation for future analytics and digital transformation. The engagement is currently focused on strategy definition and is expected to progress into platform and analytics implementation phases.

Position overview

The Senior Data Engineer supports the Data Solutions Architect during the strategy phase by validating technical assumptions and assessing the feasibility of the proposed data architecture. The role focuses on hands-on analysis of existing data assets, data pipelines, and data quality, as well as targeted proofs of concept to reduce technical and delivery risk without full production implementation.

Responsibilities

• Review and inventory existing data assets across enterprise and operational systems
• Assess data quality and availability for priority business and analytics use cases
• Validate feasibility of proposed data architecture and integration approaches
• Analyze data sourcing options from ERP, manufacturing, logistics, and BI systems
• Identify technical complexity, risks, and mitigation options
• Develop lightweight proofs of concept to validate data availability or transformation approaches
• Provide technical inputs into the implementation roadmap and sequencing

Requirements

• 5+ years of experience in data engineering within analytics-focused environments
• Hands-on expertise with Azure and Snowflake ecosystems
• Experience assessing existing data pipelines and data quality challenges
• Strong understanding of data integration, transformation, and modeling concepts
• Ability to balance hands-on technical work with strategic architecture validation
• Experience working closely with architects and strategy teams

Nice to have

• Experience in manufacturing or industrial data environments
• Familiarity with SAP ECC / SAP BW, ERP, and operational systems
• Experience with Power BI datasets, Qlik Sense, Alteryx, ExQL
• Experience contributing to strategy-phase or pre-implementation initiatives

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.

Position overview

The Data Solutions Consultant provides strategic oversight and expert advisory support throughout the Data Strategy engagement. The role ensures alignment with industry best practices, modern data and analytics trends, and proven transformation frameworks.

This position acts as a senior expert advisor across architecture, governance, operating model, and value realization topics validating strategic decisions, challenging assumptions, and guiding the team and client stakeholders on complex data transformation questions.

Responsibilities

• Provide strategic oversight across all Data Strategy workstreams (business, technology, governance, operations)
• Ensure alignment of the data strategy with industry best practices and modern data & analytics trends
• Advise on complex data governance and operating model design challenges
• Validate current-state assessment findings and strategic conclusions
• Review and challenge proposed architecture, governance, and operating model approaches
• Validate use case prioritization and value realization logic
• Advise on change management and adoption approaches for enterprise data programs
• Support risk identification and mitigation at strategy and model design level
• Contribute to and shape executive-level Data Strategy messaging and narrative
• Provide expert input into strategic principles, guardrails, and decision frameworks

Requirements

• Extensive experience in data strategy, data governance, and analytics transformation programs
• Proven advisory or consulting background in enterprise data initiatives
• Strong knowledge of industry best practices and data transformation frameworks
• Experience advising senior and executive-level stakeholders
• Ability to evaluate and validate strategic solution approaches across multiple domains
• Strong strategic thinking and structured problem-solving skills
• Experience with enterprise-scale data and analytics operating models

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

Client

Our client is one of the world’s top 20 investment companies headquartered in Great Britain, with branch offices in the US, Asia, and Europe.

Project overview

The company’s IT environment is constantly growing, with around 30 programs and more than 60 active projects. They are building a data marketplace that aggregates and analyzes data from multiple sources such as stock exchanges, news feeds, brokers, and internal quantitative systems.

As the company moves to a new data source, the main goal of this project is to create a golden source of data for all downstream systems and applications. The team is performing classic ELT/ETL: transforming raw data from multiple sources (third-party and internal) and creating a single interface for delivering data to downstream applications.

Position overview

We are looking for a Data Engineer with strong expertise in DBT, Snowflake, and modern data engineering practices. In this role, you will design and implement scalable data models, build robust ETL/ELT pipelines, and ensure high-quality data delivery for critical investment management applications.

Responsibilities

• Design, build, and deploy DBT Cloud models.
• Design, build, and deploy Airflow jobs (Astronomer).
• Identify and test for bugs and bottlenecks in the ELT/ETL solution.

Requirements

• 5+ years of experience in software engineering (GIT, CI/CD, Shell scripting).
• 3+ years of experience building scalable and robust Data Platforms (SQL, DWH, Distributed Data Processing).
• 2+ years of experience developing in DBT Core/Cloud.
• 2+ years of experience with Snowflake.
• 2+ years of experience with Airflow.
• 2+ years of experience with Python.
• Good spoken English.

Nice to have

• Proficiency in message queues (Kafka).
• Experience with cloud services (Azure).
• CI/CD knowledge (Jenkins, Groovy scripting).

Client

Our client is a large international manufacturing company listed in the S&P 500 and operating within a complex, multi‑site global environment. As part of a Data Strategy Development initiative, the organization is working to define a clear, pragmatic, and scalable data strategy aimed at improving decision‑making, reducing manual processes, strengthening data ownership, and laying a solid foundation for future analytics and digital transformation. The engagement is currently focused on strategy definition and is expected to progress into platform and analytics implementation phases.
 

Position overview

The Data Solutions Architect leads the definition of the future-state data and analytics architecture as part of the overall data strategy. The role is responsible for designing the end-to-end architectural blueprint, ensuring alignment between business objectives, governance requirements, and technology capabilities.

This position operates at a strategic and conceptual level, defining logical architecture, integration patterns, and platform standards centered on Microsoft Azure and Snowflake, without committing to physical implementation during the strategy phase.

Responsibilities

• Assess the current-state technology and data landscape across enterprise, manufacturing, logistics, and analytics systems
• Define the future-state data and analytics architecture aligned with business and governance objectives
• Design logical data integration and data flow models for a complex, multi-site environment
• Define target BI and analytics architecture supporting enterprise reporting and advanced analytics
• Establish data models, security principles, and platform standards for a scalable and governed data ecosystem
• Develop a phased data platform evolution roadmap with a focus on Azure and Snowflake
• Provide architectural inputs into the Data Governance Framework and operating model
• Contribute architecture sections to the Data Strategy Report
• Define logical data sourcing and integration approaches for enterprise systems without physical implementation commitments

Requirements

• Strong experience in enterprise data and analytics architecture
• Proven expertise with Microsoft Azure and Snowflake
• Experience designing future-state architectures in complex, global environments
• Solid understanding of data governance, security, and analytics enablement
• Ability to operate at strategy and blueprint level while grounding decisions in practical feasibility
• Experience working with senior stakeholders in high-visibility initiatives

Nice to have

• Experience with manufacturing, logistics, or industrial enterprise environments
• Familiarity with SAP ECC / SAP BW, SAP C4C, ERP and operational systems
• Experience with BI and analytics platforms such as Power BI, Qlik Sense, Alteryx
• Background in data strategy or large-scale transformation programs