Job Description
Data Engineer - Banking Domain We are seeking a motivated Data Engineer - Banking Domain to support data pipelines, data integration, and analytics platforms for banking and financial services systems. This role focuses on data ingestion, transformation, validation, and reporting support for banking datasets including customer accounts, transactions, payments, deposits, loans, cards, and compliance-related data. The ideal candidate will support ETL/ELT pipelines, write SQL queries, perform data quality checks, and collaborate with analytics, BI, business, and technology teams to support banking reporting and data needs. <> Key Responsibilities Support
ETL / ELT
data pipelines for banking and financial services data
Write SQL queries and basic Python scripts for data extraction, transformation, and validation
Assist with data ingestion from banking systems, transactional platforms, and third-party data sources
Perform data quality checks, reconciliation, and validation of customer, account, payment, and transaction data
Support data warehouse and data mart activities for banking analytics and reporting
Collaborate with BI, reporting, and analytics teams to support dashboard and regulatory reporting needs
Assist with batch processing, data mapping, schema updates, and pipeline monitoring
Support documentation of data flows, source-to-target mappings, business rules, and technical processes
Work with cross-functional teams including business analysts, QA, data analysts, and application teams
Help identify data issues, missing records, duplicate transactions, and data mismatch problems <> Required Qualifications 2-3 years of experience in data engineering, data analytics, or related data roles
Strong SQL skills for querying, joining, aggregating, and validating datasets
Basic Python knowledge for scripting, automation, and data processing
Understanding of ETL / ELT
concepts and data pipeline workflows
Exposure to cloud platforms such as AWS, Azure, or similar environments
Basic knowledge of data warehousing and dimensional modeling concepts
Experience working with structured data, transactional data, and reporting datasets
Strong analytical mindset with attention to data accuracy and quality
Good communication skills and ability to work with technical and business teams
Exposure to banking, financial services, payments, lending, or compliance data is preferred
