Senior Data Engineer

Senior Data Engineer Overview

Valtech is seeking an experienced Senior Data Engineer to help design and deliver modern cloud data platforms that support analytics, artificial intelligence, and data products across the organization. This position is focused on building scalable, production-ready data foundations that can serve both traditional analytics and advanced AI use cases. The work sits at the intersection of data, AI, creativity, and technology, and the team collaborates across disciplines to help major brands unlock new value through digital transformation.

The role is based remotely in Ukraine and is a full-time position. The application also states that candidates must currently be located in Bulgaria, Kosovo, North Macedonia, Ukraine, Poland, or Portugal because of local employment and collaboration requirements.

What you will do

• Engineer and improve cloud-based data platforms that can support analytics, AI, and internal data products at scale.
• Build dependable batch, streaming, and near-real-time data pipelines that produce curated, high-quality datasets.
• Work across structured and unstructured data sources, covering ingestion, transformation, and curation end to end.
• Design and implement modern data architectures, including lakehouse patterns and bronze, silver, and gold layering, so the platform remains reusable, scalable, and aligned with enterprise needs.
• Create data foundations that can support machine learning, causal modeling, optimization, and other production decision systems.
• Develop pipelines that enable GenAI scenarios such as large language model applications, retrieval-augmented generation, vector-based data flows, and agent-driven workflows.
• Design both logical and physical data models for analytical and operational use cases, ensuring consistency across domains.
• Set up orchestration and workflow automation using tools such as Airflow, dbt, Lakeflow, or equivalent technologies, with a strong emphasis on reliability and maintainability.
• Apply event-driven and streaming design approaches where they fit the problem.
• Strengthen governance by supporting lineage, data quality, and access control practices, including role-based and attribute-based access models.
• Introduce and maintain observability for data systems, including monitoring freshness, pipeline reliability, and SLA compliance.
• Build serving layers such as APIs, feature inputs, and analytical endpoints that can be consumed by downstream systems, including ML and AI platforms.
• Continuously improve performance, scalability, and cost efficiency across pipelines and infrastructure.
• Work closely with data scientists, machine learning engineers, analysts, and business stakeholders to translate needs into robust technical solutions.
• Support the adoption of data products and help shape best practices across the broader data and AI ecosystem.

What the company is looking for

• Strong practical experience with Apache Spark and Delta Lake.
• Excellent programming ability in Python and SQL.
• Demonstrated experience building batch and streaming pipelines and operating production-grade data platforms.
• A solid grasp of data modeling, data quality, and governance principles.
• Experience with at least one major cloud platform, with Microsoft Azure and Fabric especially relevant; AWS or GCP experience is also useful.
• Familiarity with modern data platforms such as Databricks and Snowflake.
• Experience with lakehouse architectures and distributed data systems.
• Good judgment around scalability, reliability, and performance in data pipeline design.
• A collaborative, cross-functional working style and strong problem-solving ability.
• Experience in Agile or consulting environments is considered an advantage.
• Additional experience with GenAI and AI data systems, including RAG pipelines, vector databases, and LLM data preparation, would be valuable.
• Experience with CI/CD for data pipelines and infrastructure-as-code tools such as Terraform, ARM, or CloudFormation is a plus.
• Exposure to streaming technologies such as Kafka is helpful.
• Experience optimizing Spark workloads or supporting advanced analytics and machine learning workloads, including causal analysis or experimentation platforms, is beneficial.
• Experience building data products or large-scale analytics platforms is also an advantage.
• Applicants should already be based in one of the countries listed in the application form: Bulgaria, Kosovo, North Macedonia, Ukraine, Poland, or Portugal.

Team and company context

Valtech describes itself as an experience innovation company that helps well-known global brands create better digital experiences. The organization emphasizes growth opportunities, a values-led culture, international career paths, and the chance to help shape the future of experience. It highlights a workplace built around shared values, creativity, diversity, autonomy, and global collaboration.

The company also emphasizes inclusion and accessibility. It states that candidates are evaluated on skills, experience, and potential rather than personal details such as age, gender, marital status, or a photo. If a candidate needs reasonable accommodations during interviews, they can mention this in the application or tell the talent partner.

What is offered

• Competitive pay in addition to the listed benefits.
• Medical insurance.
• A budget for sports reimbursement.
• Support for working from home.
• Free access to psychological and legal consultations.
• Support related to maternity and paternity leave.
• Internal workshops and learning opportunities.
• Reimbursement for English language classes.
• Reimbursement for professional certifications.
• Participation in local and global professional communities.
• A growth framework that helps define expectations and the steps toward the next career level.
• A mentoring program, with the option to be a mentor or a mentee.
• A progressive benefits model in Ukraine, where the package becomes richer the longer someone stays with the company.

How the application process works

After applying, the talent acquisition team reviews the submission. Candidates are asked to provide a CV that clearly shows relevant experience and expertise. The application form requests standard contact details and also asks for current location, notice period or availability, whether the candidate has an open private entrepreneur arrangement for future collaboration, salary expectations in EUR gross for full-time B2B collaboration, English level, years of hands-on data engineering experience, cloud-platform experience, experience with Spark and Delta Lake in a lakehouse setup, and an example of a production pipeline along with the hardest technical trade-off made in that system.

The company notes that it does not require age, gender, marital status, or a headshot as part of the application. It also warns applicants to be aware of recruitment fraud.

Valtech presents this role as an opportunity to work on meaningful, technically challenging data and AI systems in a collaborative, international environment, with room for learning, growth, and long-term development.

Degree Requirement: Not Specified

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