Senior/Lead Data Engineer

N-iX is a global software development company founded in 2002, connecting over 2,400+ tech professionals across 40+ countries. They deliver innovative technology solutions in cloud computing, data analytics, AI, embedded software, IoT, and more to global industry leaders and Fortune 500 companies.

The client is a leading European online car marketplace, connecting buyers and sellers across 18 countries with over 30 million monthly users, making it one of the largest digital marketplaces for vehicles in Europe.

• Hands-on data engineering experience building and operating production data pipelines, ideally within analytics-driven environments.
• Strong SQL skills.
• Experience with data modeling for analytics, including fact and dimension tables.
• Experience with workflow orchestration, preferably Airflow.
• Experience working with AWS-based data environments, particularly Athena and AWS Data Lake.
• Experience with data validation, testing, and troubleshooting.
• Strong sense of ownership and engineering judgment: comfortable working with incomplete requirements, proactively seeking context, challenging assumptions when appropriate, and looking for practical solutions rather than stopping at the first blocker.
• Excellent verbal and written English skills, with clear communication across data analysts, engineers, and business stakeholders.

Nice to have:

• Experience with data mesh architectures or working in a data mesh environment.
• Experience with marketplace, web/app, or digital analytics data.
• Experience with DBT and/or Snowflake.
• Familiarity with AI-assisted engineering tools such as Codex.

• Maintain, troubleshoot, and improve existing data pipelines, and build new pipelines and datasets based on analytics and business requirements.
• Design and maintain analytical data models, including fact and dimension models.
• Ingest and integrate data from different source systems into the AWS Data Lake.
• Build, deploy, validate, monitor, and, when necessary, backfill data pipelines.
• Partner with data analysts to understand their requirements and provide reliable, easy-to-use datasets.
• Clarify requirements with business stakeholders rather than implementing ambiguous requests as-is.
• Ensure data quality through appropriate validation and testing, investigating data and pipeline issues and taking ownership of finding pragmatic solutions end to end.
• Use AI-assisted development tooling effectively while critically reviewing and validating generated solutions.

N-iX Krakow, ​Zabłocie Business Park business centre, Zabłocie 43A, 30-70