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Valtech Logo Valtech · IT - Software Development

Senior Data Engineer

Ukraine · Job Posted June 15, 2026
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Job Description

Senior Data Engineer - UKRAINE - REMOTE. We are looking for an experienced Senior Data Engineer to design, build, and optimize modern, cloud-based data platforms that power analytics, AI, and data products across the organization. You will work on scalable batch, streaming, and near-real-time pipelines, enabling high-quality, curated datasets while ensuring robust data governance, security, and observability across the data ecosystem. You will also play a key role in supporting AI and GenAI systems, enabling pipelines for machine learning, causal modeling, and LLM-powered applications such as RAG and agent-based systems. Our preferred platforms are Microsoft Azure / Fabric (primary), GCP, AWS, Databricks, and Snowflake, with Azure experience being highly transferable to Fabric. You will collaborate closely with data scientists, ML engineers, and platform teams to ensure the data foundation supports production-grade, decision-oriented AI systems.

Job Responsibility

  • Build & Data Platform Engineering: design and implement scalable data platforms and pipelines across cloud environments
  • develop reliable batch, streaming, and near-real-time pipelines using technologies such as Spark and Delta Lake
  • build ingestion, transformation, and curation workflows for both structured and unstructured data
  • implement modern data architectures including lakehouse patterns and medallion layering (bronze, silver, gold)
  • Enable AI, GenAI & Data Products: deliver high-quality datasets that support analytics, machine learning, causal modeling, and optimization systems
  • enable data pipelines for GenAI use cases (including LLMs, RAG pipelines, and vector-based data flows) and agent-based architectures and intelligent workflows
  • Data Modeling, Orchestration & Automation: design scalable logical and physical data models for analytical and operational use cases
  • orchestrate workflows using tools such as Airflow, dbt, Lakeflow, or equivalents
  • Architecture, Governance & Observability: apply modern architecture patterns including event-driven and streaming architectures
  • ensure adherence to best practices in data governance, lineage, quality, and access control (RBAC/ABAC)
  • establish strong data observability including monitoring of data freshness, pipeline reliability, and SLA adherence
  • Data Serving, Integration & Optimization: enable data serving layers (APIs, feature inputs, analytical endpoints) to support downstream systems
  • continuously monitor and optimize pipelines and infrastructure for performance, scalability, and cost efficiency
  • Collaboration: work closely with data scientists, ML engineers, analysts, and business stakeholders to translate requirements into robust data solutions
  • support adoption of data products and contribute to best practices across the data and AI ecosystem

Requirements

  • Strong hands-on experience with Apache Spark and Delta Lake
  • strong programming skills in Python and SQL
  • proven experience building batch and streaming data pipelines and production-grade data platforms
  • solid understanding of data modeling, data quality, and governance principles
  • experience with one or more major cloud platforms, with preference for Microsoft Azure / Fabric, as well as AWS or GCP
  • familiarity with modern data platforms such as Databricks and Snowflake
  • experience with lakehouse architectures and distributed data systems
  • strong understanding of scalability, reliability, and performance considerations in data pipelines
  • strong problem-solving skills focused on scalability and reliability
  • collaborative approach to working in cross-functional teams
  • experience in Agile or consulting environments is beneficial

Nice to have

  • Experience with GenAI and AI data systems (e.g., RAG pipelines, vector databases, LLM data preparation)
  • CI/CD for data pipelines and infrastructure-as-code tools such as Terraform, ARM, or CloudFormation
  • exposure to streaming technologies (e.g., Kafka)
  • Spark optimization
  • advanced analytics and ML workloads (including causal or experimentation platforms)
  • experience building data products or large-scale analytics platforms

What we offer

  • Mental and physical health: Medical insurance
  • Sports reimbursement budget
  • Home office support
  • A number of free psychological and legal consultations
  • Maternity and paternity leave support
  • Personal and professional development: Internal workshops and learning initiatives
  • English language classes compensation
  • Professional certifications reimbursement
  • Participation in professional local and global communities
  • Growth Framework to manage expectations and define the steps to move towards the selected career
  • Mentoring program with the ability to become a mentor or a mentee to grow to a higher position
  • Valtech Ukraine has a system of progressive benefits packages in place — the longer you stay with the company — the more benefits you get
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