Data Engineer

About this role

About the role: - You will design, build and maintain data pipelines that move information reliably from multiple sources into centralized storage systems - Your work spans extracting raw data, transforming it to match business requirements, and loading it into repositories ready for analysis - You will ensure data quality and consistency across the infrastructure you own - You will monitor pipeline performance and troubleshoot failures to keep data flowing without interruption What you'll work on: - ETL workflows using Python and SQL to process structured and unstructured data at scale - PySpark jobs for distributed data processing across large datasets - AWS services to build robust data architectures, with particular depth in Redshift for analytics - Data lake and data warehouse designs that organize information efficiently - Orchestration of complex workflows using tools like Airflow - Modern data platforms including Databricks or Snowflake for advanced transformations What we're looking for: - Proficiency in Python and SQL, demonstrated through real projects - Hands-on experience building and optimizing PySpark applications - Proven track record designing and running ETL and data pipeline systems - Deep experience working with AWS services in production environments - Practical exposure to AWS Redshift for data warehousing and analytics - Familiarity with Databricks or Snowflake platforms - Understanding of data lake and data warehouse concepts and implementation - Knowledge of Airflow for workflow orchestration is valued - Background in FinTech, Banking, BFSI, or Financial Services Good to know: - Immediate joiners only