Senior Data Engineer

North Macedonia - Remote · Bulgaria · North Macedonia · Poland · Portugal · Posted Oct 6, 2026

At a glance

Location: North Macedonia - Remote · Bulgaria · North Macedonia · Poland · Portugal

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, we help brands unlock new value in an increasingly digital world.
At the intersection of data, AI, creativity, and technology, we drive transformation for leading organizations, including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more.
At Valtech, we don’t just talk about transformation. We make it happen. Our people are the heart of our success, and we foster a workplace where everyone has the support to thrive, grow and innovate.
Are you ready to create what’s next? Join us.

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.
Beyond technical delivery, we're looking for someone genuinely curious about the business problems behind the data to help derive and shape business requirements.
This role can be delivered on either of our two core cloud ecosystems — AWS or Azure/Fabric — and you'll be staffed on projects that match your strongest platform.

Design and implement scalable data platforms and pipelines on AWS or Azure/Fabric.
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 within Databricks or Fabric.
Deliver high-quality datasets that support analytics, machine learning, causal modeling, and optimization systems.
Design scalable logical and physical data models for analytical and operational use cases.
Orchestrate workflows using tools such as Airflow, dbt, Databricks Workflows, or Azure Data Factory.
Ensure adherence to best practices in data governance, lineage, quality, and access control.
Establish strong data observability, including monitoring of data freshness, pipeline reliability, and SLA adherence.
Collaborate closely with data scientists, ML engineers, analysts, and business stakeholders to translate requirements into robust data solutions.

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.
Demonstrable hands-on experience with either AWS data services and the Databricks Lakehouse Platform or Microsoft Azure / Fabric.
Experience with lakehouse architectures and distributed data systems.
Strong understanding of scalability, reliability, and performance considerations in data pipelines.
Naturally curious with strong problem-solving skills focused on scalability and reliability.

Familiarity with other modern data platforms such as Snowflake or GCP
Deep expertise in both AWS and Azure/Fabric tracks
Experience with GenAI and AI data systems
Experience with CI/CD for data pipelines
Experience with infrastructure-as-code tools such as Terraform or CloudFormation
Additional exposure to streaming technologies such as Kafka
Spark optimization, or advanced analytics and ML workloads
Experience building data products or large-scale analytics platforms

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