Description:

Mandatory Skills:
Strong understanding of Corporate Banking data domains including Customers, Facilities, Limits, Collateral, Covenants, Ratings, and Credit Applications.
Solid hands-on experience in designing, developing, and managing ETL/ELT pipelines for enterprise-scale data platforms.
Advanced proficiency in SQL for data extraction, transformation, reconciliation, and performance optimization.
Hands-on experience in Python and Spark for data engineering and automation.
Strong experience with Azure Data Factory, Azure Databricks, Azure Storage, and related Azure data services.
Experience working with Cloudera/Hadoop ecosystem including HDFS, Hive, Spark, and Impala.
Experience building and supporting Data Lakes, Data Warehouses, and Enterprise Data Platforms.
Strong experience in data modelling, source-to-target mappings, data transformation, and data integration.
Knowledge of data quality, data governance, metadata management, and data security best practices.
Strong analytical and problem-solving skills with experience supporting banking data platforms.
Desired Skills
Experience supporting Corporate Banking, Credit Risk, Lending, ELCM, or Limit Management platforms.
Experience with CI/CD, DevOps, Git, Jenkins, or deployment automation.
Working knowledge of Databricks Unity Catalog and modern data architecture patterns.
Exposure to enterprise data platforms.
Experience supporting AI, Analytics,



or Data Science consumption layers.

Roles & Responsibilities:
Data Pipeline Management Design, build, and maintain scalable ETL/ELT pipelines for Corporate Banking and Credit Risk data.
Data Integration Integrate data from multiple source systems and deliver curated datasets for business consumption.
Data Transformation Develop transformation logic and reusable frameworks using Spark, Databricks, and Python.
Performance Optimization Optimize jobs, queries, and data pipelines for reliability and scalability.
Data Quality Implement automated validation checks and reconciliation controls.
Production Support Troubleshoot data issues, perform RCA, and ensure platform stability.
Collaboration Work closely with Data Analysts, Architects, Business Teams, and Vendors.
Documentation Maintain technical specifications, mappings, lineage, and operational procedures.

Overall years of experience 8+ years of experience in Data Engineering and Enterprise Data Platforms. Relevant years of experience 5+ years of hands-on experience with SQL, Hadoop/Cloudera, Azure Data Platform, Databricks, Python, and Spark. Industry & Education background Bachelor's degree in Computer Science, Information Technology, Engineering, or related field. Experience in Banking, Corporate Banking, Risk, or Financial Services preferred.

Enable Skills-Based Hiring No

📌 Lead Data Engineer (Karnataka)
🏢 LanceSoft Europe
📍 Karnataka