Data Engineer & AI - ETL - (Banking Project)

Job Description:

• Design, develop, and maintain data engineering solutions to support data generation, collection, integration, and processing across multiple systems.
• Build, optimize, and maintain scalable and reliable data pipelines to support data analytics, AI, and business intelligence initiatives.
• Develop and implement ETL (Extract, Transform, Load) processes to migrate, transform, and deploy data across different platforms and systems.
• Perform data integration from various internal and external sources while ensuring data accuracy, consistency, completeness, and quality.
• Monitor data pipeline performance, troubleshoot data processing issues, and implement improvements to enhance reliability and efficiency.
• Collaborate with data scientists, AI engineers, business analysts, and other stakeholders to understand data requirements and deliver appropriate data solutions.
• Apply data engineering best practices, including data validation, error handling, documentation, and workflow automation.
• Support the development and maintenance of data infrastructure for AI and machine learning use cases.
• Ensure data solutions comply with applicable data governance, security, privacy, and regulatory requirements, particularly in financial services environments.
• Work closely with business and technical teams to translate business requirements into effective data engineering solutions.

Requirements:

• Minimum Bachelor’s Degree (S1) in Computer Science, Information Technology, Data Science, Software Engineering, or a related field.
• 5–7 years of professional experience in data engineering, data development, or a closely related technical role.
• Experience in the banking or financial services industry is highly preferred.
• Experience working at a consulting firm or technology consulting company is an advantage.
• Strong understanding of data engineering concepts, including data integration, data transformation, data processing, and data pipeline development.
• Hands-on experience developing and maintaining ETL/ELT processes and managing data migration across systems.
• Proficiency in SQL and experience working with relational databases and/or data warehouses.
• Experience with programming or scripting languages such as Python, Java, or Scala.
• Familiarity with data pipeline orchestration and workflow automation tools such as Apache Airflow or equivalent platforms.
• Understanding of data quality management, data validation, data governance, and data security principles.
• Familiarity with cloud-based data platforms and big data technologies is an advantage.
• Strong analytical and problem-solving skills, with the ability to troubleshoot complex data processing issues.

Preferred Candidate Profile:

• Candidates with relevant experience delivering data engineering solutions for banking, financial institutions, or other regulated financial services organizations.
• Candidates with experience supporting AI, machine learning, analytics, or enterprise data platform initiatives.

Skills: Database Systems, Data Engineering, Python, Data Integration, Microsoft SQL Server, Data Processing, MongoDB, Redis, ETL, Hadoop