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.

Desired Candidate Profile 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.