Data Engineering Lead

Job Description

Key Responsibilities

• Design, build, and maintain data pipelines using Airflow for orchestration
• Develop and maintain data models and transformations in dbt
• Own data warehousing architecture in BigQuery, including performance, cost, and schema design
• Write production-quality Python for ETL/ELT, tooling, and automation
• Deploy and manage workloads using Kubernetes and GCP
• Monitor pipeline health and system performance using Grafana
• Partner with analytics, product, and engineering stakeholders to understand data needs and translate them into reliable pipelines
• Troubleshoot and resolve data quality issues and pipeline failures
• Contribute to technical decisions on data architecture and tooling

Qualifications

• Experience

• 5+ years of experience in data engineering
• Strong hands-on experience with dbt, Airflow, and BigQuery – these are core to the role
• Solid Python skills for building and maintaining data pipelines
• Experience with GCP and Kubernetes
• Familiarity with monitoring/observability tools (e.g. Grafana)
• A track record of taking ownership of systems end-to-end
• Experience with streaming technologies such as Kafka and Flink is a plus
• Excellent communication skills with the ability to collaborate across technical and non-technical teams.
• Ability to thrive in a fast-paced, international environment.

• Skills

• Analytical and problem-solving skills, with the ability to translate business needs into technical solutions.
• Strong communication and interpersonal skills, with experience in stakeholder management and cross-functional collaboration.
• Ability to prioritize features and enhancements based on business value and customer impact.

Are you interested in this position?
Apply by clicking on the “Apply Now” button below!
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