Senior Data Engineer

Valtech is the experience innovation company that exists to unlock a better way to experience the world. By blending crafts, categories, and cultures, they help brands unlock new value in an increasingly digital world. They drive transformation for leading organizations including L’Oréal, Mars, Audi, P&G, Volkswagen Dolby, and more.

Technical skills:

• 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.

Cloud & Platforms (Key Requirement):

• Experience with one or more major cloud platforms, preferably Microsoft Azure / Fabric, AWS, or GCP.
• Familiarity with modern data platforms such as Databricks and Snowflake.

Architecture & Systems Thinking:

• Experience with lakehouse architectures and distributed data systems.
• Strong understanding of scalability, reliability, and performance considerations in data pipelines.

Mindset:

• 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 qualifications:

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

Build & Data Platform Engineering:

• Design and implement scalable data platforms and pipelines across cloud environments (Azure/Fabric, AWS, GCP, Databricks, Snowflake).
• Develop reliable batch, streaming, and near-real-time pipelines using technologies such as Spark and Delta Lake.
• Build ingestion, transformation, and curation workflows for 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 supporting analytics, machine learning, causal modeling, and optimization systems.
• Enable data pipelines for GenAI use cases including LLMs, RAG pipelines, vector-based data flows, 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, focusing on automation, reliability, and maintainability.

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 including ML and AI platforms.
• 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.

This is a position based in Poland. Beware of recruitment fraud. Valtech is committed to inclusion and accessibility and provides reasonable accommodations during the interview process upon request.