2 months ago
Prague, CzechiaMid Level
Responsibilities
- Build and operate enterprise-scale data pipelines processing more than 100,000 monthly tasks across campaigns, customer analytics, and e-commerce recommendations.
- Own and maintain shared Customer Data Platform components supporting analytics, e-commerce, and partner management domains.
- Build AI-powered data platforms with MLOps frameworks, automated monitoring, and self-healing pipeline capabilities.
- Enrich datasets with new data sources and integrate data science outputs into business channels.
- Develop automation using AI coding assistants and agentic frameworks to reduce repetitive engineering work.
- Engineer frameworks for managing AI agents that deliver insights from integrated datasets to end users.
- Implement DevOps practices and environment optimization initiatives targeting 99% uptime across more than 200 database schemas.
- Resolve incidents systematically and support cross-platform data integration.
- Translate business requirements into technical specifications and present insights to stakeholders.
Requirements
- At least 3 years of applied data engineering experience.
- Strong SQL skills, including complex joins, subqueries, data warehousing, ETL/ELT, and data modeling.
- Expertise in Python for data wrangling, object-oriented programming, and large-scale automation.
- Experience with cloud data platforms; Azure knowledge is a plus.
- Knowledge of Databricks, including Unity Catalog, workflows, and compute management.
- Proficiency with Apache Spark and PySpark, including distributed processing, DataFrame operations, Spark SQL, and Databricks integration.
- Experience with DevOps practices, automated testing, version control, and deployment strategies.
- Strong stakeholder communication and technical specification skills.
- Systematic problem-solving and cross-platform integration experience.
- A BSc, MSc, or PhD in Computer Science, AI, or a related STEM field is a plus.
Benefits
- Hybrid working mode with 3 days in the office and 2 days remote.
- Work on large-scale, production-ready AI systems using modern cloud-based tools.
- Professional and personal growth opportunities in AI and data engineering.
- Elective benefits tailored to the employee’s country.
- Leadership, professional development, and on-demand learning programs.
- Financial, physical, and mental well-being support through seminars, events, and the global Life Empowerment Assistance Program.
- Inclusive employee communities, business resource groups, volunteering, environmental, and social initiatives.
- Onboarding program connecting new coworkers within the first 30 days.
Tech Stack
Categories
Data Engineering
About TD SYNNEX
TD SYNNEX distributes IT hardware, software, and cloud services and aggregates solutions for technology vendors and resellers, including VARs and system integrators. It provides logistics, financing, cloud marketplaces, and professional services that help partners procure, bundle, and deploy technology for end customers. The public company (NYSE: SNX), headquartered in Fremont, California, was formed in 2021 through the merger of Synnex and Tech Data and operates globally.