Senior Data Engineer

What you'll do

• Lead the design and development of scalable, high-performance data pipelines and infrastructure
• Resolve complex technical issues creatively and effectively
• Lead design, build, and maintenance of high-scale production datasets with versioned outputs and reliable reports
• Manage end-to-end lifecycle of data features including schema evolution, business logic updates, and safe rollouts
• Architect scalable and efficient solutions for data ingestion, transformation, and storage ensuring performance, reliability, and security
• Drive down compute and storage costs proactively
• Serve as technical lead for production incidents, investigate root causes, implement fixes, and validate data recovery
• Network and advise others on complex matters across disciplines
• Mentor and guide engineers to foster a culture of technical excellence
• Enhance monitoring and observability of data processes to improve debugging, error detection, and system reliability

Requirements

• 8+ years of related experience with a Bachelor’s degree (or 6 years with a Master’s; 3 years with a PhD)
• Advanced knowledge of Python
• Deep understanding of distributed data processing frameworks like Apache Spark or PySpark
• Expertise in Apache Airflow and Databricks for orchestration and scalable data processing
• Extensive experience with cloud-based data infrastructure (AWS, GCP) and modern data lake architectures
• Strong knowledge of data modeling, database design, and query optimization for both relational and non-relational databases
• Proven track record of driving best practices for code quality, testing, and software design in a data engineering context
• Ability to adapt communication style and use persuasion when delivering messages related to wider business

Tech stack

Benefits