Data Engineer

Key Responsibilities

• Design, develop, and maintain data pipelines for data extraction, transformation, and loading (ETL/ELT).
• Develop and optimize SQL queries, stored procedures, and database operations.
• Work with structured and unstructured data from multiple sources.
• Build and maintain data integration workflows and data warehouse solutions.
• Ensure data quality, consistency, security, and reliability.
• Monitor and troubleshoot data pipelines and resolve data-related issues.
• Collaborate with data analysts, data scientists, software developers, and business teams.
• Optimize data processing performance and improve existing data workflows.
• Document data processes, technical specifications, and data models.

Required Skills

• Strong proficiency in SQL and database technologies.
• Hands-on experience with ETL/ELT tools and data integration.
• Experience with Python for data processing and automation.
• Knowledge of data warehousing, data modelling, and database optimization.
• Experience with relational databases such as Oracle, SQL Server, or PostgreSQL.
• Familiarity with cloud data platforms such as AWS, Azure, or Google Cloud.
• Knowledge of data pipeline orchestration tools such as Apache Airflow is an advantage.
• Understanding of data security, governance, and data quality practices.

Preferred Qualifications

• Experience in the banking or financial services industry.
• Exposure to big data technologies such as Apache Spark or Hadoop.
• Experience with cloud-based data platforms such as Snowflake, Databricks, or Azure Data Factory.
• Bachelor's degree in Computer Science, Information Technology, or a related field.