Data Engineer

We are seeking a skilled and motivated Data Engineer, specialized in developing, managing the architecture, infrastructure, and tools necessary for collecting, storing, processing large volumes of data. The Data Engineer will play a key role in ensuring that data pipelines are efficient, scalable, and reliable, enabling organizations to make informed decisions based on data-driven insights.

Key Responsibilities & Accountabilities:

Database Development:

• Develop stored procedure, views, functions, partitions, etc., using SQL Server.

ETL Development:

• Develop, code, test, and debug using SSIS ETL (SQL Server Integration Services). Translate complex business requirements into technical solutions. Validate ETL design and ensure completeness of business specifications.

Production Support:

• Troubleshoot ETL jobs in Production Support. Apply strong analytical and problem-solving skills in a Production Support environment.

Technical Skills:

• Demonstrate proficiency in .NET with C#.NET and VB.NET.

Database Hosting and Management:

• Host and manage online databases to ensure accessibility and reliability. Oversee database administration tasks and optimizations.

MIS Structure Maintenance:

• Load and maintain Management Information System (MIS) structures related to incorporating external sources (e.g., Cloud, other countries). Explore and implement possible extensions in existing modules.

Enterprise Scheduling Parameterization:

• Contribute to the parameterization of enterprise scheduling processes.

Requirements

Education:

• Bachelor's or higher degree in Information Technology or equivalent work experience.

Database Management Systems:

• Hands-on development experience with database management systems, specifically Microsoft SQL Server 2012 and above, Oracle knowledge will be considered as a plus.

ETL Tools:

• Hands-on development experience with ETL (Extract, Transform, Load) tools, specifically SSIS.

Performance Tuning:

• Hands-on experience in performance tuning, particularly in handling large volumes of data and table partitioning.

Data Modeling Concepts:

• Proficiency in Data Warehousing and Data Mining techniques. Familiarity with dimensional data modeling concepts, including dimensions and fact tables, surrogate keys, and star and snowflake schema.

Soft Skills:

• Excellent communication and interpersonal skills. Demonstrated ability to handle high-pressure situations.

Domain Knowledge (Optional):

• Knowledge of banking subject areas such as Customers, Deposits, Loans, Cards, and Wealth Management.

Certification (Optional):

• Microsoft Certification is added value.