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Valtech is a global digital agency that helps organizations improve customer experiences and advance their digital businesses. Its work brings together technology, marketing, data, and AI to support commerce initiatives, enterprise digital transformation, and stronger marketing performance. With teams and offices around the world, Valtech partners with companies on digital strategy, experience innovation, and the practical use of data to shape more effective digital futures.
Senior Data Engineer - Poland Remote
Join Valtech as a Senior Data Engineer building cloud data platforms that support analytics, machine learning, GenAI, and production data products. You will develop scalable pipelines, lakehouse architectures, and reliable data services for modern AI and analytics workloads.
Description
- Architect, develop, and optimize cloud data platforms for analytics, AI, and data products.
- Create dependable batch, streaming, and near-real-time pipelines for structured and unstructured data.
- Develop robust processes for data ingestion, transformation, and curation.
- Build lakehouse solutions and medallion-layer architectures with Databricks or Microsoft Fabric.
- Produce trusted datasets for analytics, machine learning, causal analysis, optimization, GenAI, LLM, RAG, and agent-based applications.
- Create data models and automate workflow orchestration with Airflow, dbt, Databricks Workflows, Azure Data Factory, or comparable tools.
- Use event-driven and streaming patterns while establishing governance, lineage, quality controls, access management, and observability.
- Track data freshness, pipeline resilience, SLA performance, scalability, efficiency, and operating costs.
- Provide serving layers, APIs, feature inputs, and analytical interfaces for downstream machine learning and AI solutions.
- Clarify and improve business needs through stakeholder discovery and informed recommendations.
- Partner with data scientists, machine learning engineers, analysts, platform teams, and business stakeholders.
- Help teams adopt data products and advance data and AI engineering practices.
Requirements
- Demonstrated hands-on experience with Apache Spark and Delta Lake.
- Strong Python and SQL programming capabilities.
- Professional experience delivering batch and streaming pipelines and production-ready data platforms.
- Sound knowledge of data modeling, data quality, and data governance.
- Substantial practical experience with either AWS data services and Databricks Lakehouse or Microsoft Azure/Fabric and related tools.
- Deep expertise in one cloud and platform path; Snowflake or GCP knowledge is advantageous but not required.
- Experience designing lakehouse architectures and working with distributed data systems.
- Strong grasp of scalability, reliability, and performance requirements for data pipelines.
- Effective problem-solving abilities and a collaborative working style.
- Experience in Agile or consulting environments is an advantage.
- Experience with GenAI and AI data platforms, data-pipeline CI/CD, Terraform or CloudFormation, Kafka, Spark optimization, advanced analytics or machine learning workloads, or large-scale data products is desirable.
- Submit a CV detailing relevant experience and expertise.
Benefits
- 24 paid working days of annual vacation.
- National holidays are covered.
- Sick leave of up to 20 days per year.
- Unpaid leave of up to 20 days per year.
- Medical insurance.
- Choice of a Multisport card or Multikafeteria.
- Support for maternity and paternity leave.
- Internal workshops and learning initiatives.
- Reimbursement for professional certifications.
- Opportunities to participate in local and global professional communities.
- A Growth Framework for setting expectations and planning progression toward a chosen career path.
- A mentoring program offering opportunities to develop as either a mentor or mentee and progress toward a higher position.
- Progressive benefits packages that expand with length of service.
- Flexible remote and hybrid work options, subject to country-specific availability.
- Career progression through international mobility and professional development programs.
- Access to modern tools, training, and industry experts.
- Reasonable accommodations throughout the interview process.
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