Senior Data Engineer
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Job Description
Senior Data Engineer building cloud data platforms for Valtech, an experience innovation company transforming brands through data, AI, creativity, and technology. Enabling analytics, ML, GenAI, and production-grade data products.
Responsibilities:
- Design, build, and optimize modern cloud-based data platforms powering analytics, AI, and data products
- Develop reliable batch, streaming, and near-real-time pipelines for structured and unstructured data
- Build ingestion, transformation, and curation workflows
- Implement lakehouse architectures and medallion layering in Databricks or Fabric
- Deliver high-quality datasets for analytics, machine learning, causal modeling, optimization, GenAI, LLM, RAG, and agent-based systems
- Design data models and orchestrate automated workflows using Airflow, dbt, Databricks Workflows, Azure Data Factory, or equivalents
- Apply event-driven and streaming architectures and implement data governance, lineage, quality, access control, and observability
- Monitor data freshness, pipeline reliability, SLA adherence, performance, scalability, and cost efficiency
- Enable data serving layers, APIs, feature inputs, and analytical endpoints for downstream ML and AI systems
- Discover and refine business requirements through stakeholder analysis and experience-based recommendations
- Collaborate with data scientists, ML engineers, analysts, platform teams, and business stakeholders
- Support adoption of data products and contribute to data and AI ecosystem best practices
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
- Strong, demonstrable hands-on experience with either AWS data services and the Databricks Lakehouse Platform, or Microsoft Azure/Fabric and associated data tools
- Deep expertise in one cloud/platform track; Snowflake or GCP familiarity is a plus but not required
- Experience with lakehouse architectures and distributed data systems
- Strong understanding of scalability, reliability, and performance considerations in data pipelines
- Strong problem-solving skills and collaborative approach
- Experience in Agile or consulting environments is beneficial
- GenAI and AI data systems experience, CI/CD for data pipelines, Terraform or CloudFormation, Kafka, Spark optimization, advanced analytics/ML workloads, or large-scale analytics/data products are nice to have
- CV covering relevant experience and expertise
Benefits:
- 24 working days of paid vacation
- National holidays covered
- Sick leave (up to 20/year)
- Unpaid leave (up to 20/year)
- Medical insurance
- Multisport card OR Multikafeteria
- Maternity & paternity leave support
- Internal workshops & learning initiatives
- Professional certifications reimbursement
- Participation in professional local & 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
- Progressive benefit packages—the longer you stay with the company, the more benefits you get
- Flexibility, with remote and hybrid work options (country-dependent)
- Career advancement, with international mobility and professional development programs
- Access to cutting-edge tools, training and industry experts
- Reasonable accommodations during the interview process
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