Senior Data Engineer

Key Responsibilities

• Design, develop, and maintain scalable and reliable ETL/ELT data pipelines.
• Integrate and transform data from multiple internal and external sources.
• Ensure data accuracy, consistency, and availability across analytics and operational platforms.
• Optimize data processing workflows for performance, scalability, and efficiency.
• Develop and maintain data models and schemas that support reporting and analytical requirements.
• Write, optimize, and troubleshoot complex SQL queries and data transformations.
• Collaborate with business stakeholders and technical teams to understand and translate data requirements into robust solutions.
• Monitor, troubleshoot, and resolve data-related issues to maintain data integrity and system reliability.
• Support cloud-based data platforms and contribute to data architecture improvements.
• Implement best practices for data governance, security, and quality management.
• Identify opportunities for automation and continuous improvement within the data environment.
• Document data processes, workflows, and technical solutions to support operational excellence.

Minimum Requirements

Qualifications

• Bachelor's Degree in Computer Science, Information Technology, Engineering, or a related field.
• Equivalent practical experience will also be considered.

Experience

• Minimum of 4 years' experience in a Data Engineering, Data Management, or similar role.
• Proven experience designing, building, and maintaining enterprise data pipelines.
• Experience working within modern analytics and data warehousing environments.

Technical Skills

• Strong proficiency in Python for data engineering, automation, and data processing.
• Advanced SQL skills, including data extraction, transformation, optimization, and performance tuning.
• Hands-on experience building and maintaining ETL/ELT processes and frameworks.
• Experience working with ETL/ELT tools such as Apache Airflow, Talend, or similar technologies.
• Familiarity with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform (GCP).
• Strong understanding of data modelling, database design, and schema architecture.
• Experience with Big Data technologies such as Hadoop, Apache Spark, ClickHouse, or similar platforms.
• Understanding of data integration, data quality, and data governance principles.

Apply now!