Data Engineering Team Lead

What you'll do

• Lead and scale two specialized sub-teams (Data Quality and Feature Engineering), managing performance, career development, and hiring
• Design scalable, highly available data pipelines bridging big data storage and real-time machine learning inference
• Establish rigorous standards for data observability, implementing automated monitoring and alerting for complex data ingestion services
• Define and enforce policies for data privacy, security, and lifecycle management, ensuring compliance with regulations and company standards
• Oversee development and optimization of high-throughput features using Scala to aggregate data for Redis Cluster
• Coordinate with infrastructure team to ensure execution of complex data workflows and DAGs using Apache Airflow
• Monitor global deployments ensuring stability, reliability, and performance of production systems following 'you build it, you run it' philosophy
• Partner with Chief Data Officer to align technical strategies with business objectives and machine learning roadmaps
• Collaborate closely with CTO for technical solutions and strategy, and with CPO on product integration and transversal projects

Requirements

• 6+ years of experience in software or data engineering
• At least 2 years in a formal leadership or management role building high-throughput distributed systems
• Advanced knowledge of Spark and ability to conduct deep code reviews
• Proven track record designing and optimizing complex batch and streaming pipelines using Apache Spark
• Advanced SQL knowledge
• Experience with cloud environments (AWS), particularly EMR, EC2, Athena, and S3
• Strong ability to debug complex distributed systems and drive root-cause analysis for production issues
• Excellent communication skills in English
• Legal permit to work in Spain (no visa sponsorship provided)

Tech stack

Benefits