Middle Data Engineer

• Develop, maintain, and optimize data pipelines using SQL and ETL processes.
• Extract, transform, and integrate data from multiple sources to support business and analytical needs.
• Manage and process large-scale datasets within a secure data environment.
• Ensure data quality, accuracy, and consistency to support reliable reporting and analysis.
• Collaborate with business and product teams to deliver actionable data insights that support customer relationship management and lifecycle marketing initiatives.

• Develop, maintain, and optimize data pipelines using SQL and ETL processes.
• Extract, transform, and integrate data from multiple sources to support business and analytical needs.
• Manage and process large-scale datasets within a secure data environment.
• Ensure data quality, accuracy, and consistency to support reliable reporting and analysis.
• Collaborate with business and product teams to deliver actionable data insights that support customer relationship management and lifecycle marketing initiatives.

Minimum Qualifications

• Bachelor’s degree (S1) in Computer Science, Information Technology, Information Systems, Data Science, or a related field.
• Minimum of 3 years of professional experience in Data Engineering or a similar role. Experience in the banking or financial services industry is a strong advantage, particularly in handling large-scale and secure data environments.
• Proficiency in SQL and ETL processes and tools. Experience working in a Cloudera Hadoop environment is a significant advantage.
• Strong analytical skills and attention to detail, with the ability to interpret data and understand customer behavior. An interest in customer relationships and lifecycle marketing is highly desirable.
• Ability to translate complex data insights into clear, actionable recommendations for business and product stakeholders.