Data Engineer

About this role

About the role: - Design and construct data pipelines capable of handling high volumes of data across production environments - Develop ETL and ELT frameworks to process, move and transform data at scale - Engineer solutions for batch processing workloads and real-time data streaming - Maintain data quality through validation checks, monitoring and remediation of issues in live systems - Optimize query performance and data storage across warehouses and lakes - Troubleshoot pipeline failures and performance bottlenecks in production What you'll work on: - Building robust extraction, transformation and loading processes for enterprise datasets - Working with distributed processing frameworks and modern data platforms - Collaborating across engineering teams, analytics functions and business stakeholders to deliver data infrastructure - Implementing data models that support both analytical and operational use cases - Creating monitoring and alerting systems to track pipeline health and data freshness What we're looking for: - 4–6 years of experience in data engineering or a closely related field - Advanced proficiency in SQL and Python for data manipulation and pipeline development - Hands-on experience building and maintaining ETL and ELT systems - Working knowledge of cloud platforms including AWS, Azure or GCP - Familiarity with distributed data processing tools such as Spark, Databricks or Kafka - Experience with data warehouse or data lake technologies and orchestration tools like Airflow or Snowflake - Strong analytical skills and the ability to debug complex data issues - Clear communication and teamwork across technical and non-technical stakeholders