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.