Data Engineer (PySpark, Informatica BDM, ETL, Banking)

Role: Data Engineer

Location: Bengaluru or Chennai (2-3days/week On-Site)

Job Type: Permanent

Job Description:

• We are seeking a highly skilled Data Engineer with 6+ years of experience in building and optimizing data pipelines and data integration solutions.
• The ideal candidate should have strong hands-on experience with PySpark as a primary skillset, along with Informatica BDM (Big Data Management) expertise.
• Prior experience working within the banking or financial services domain is essential.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines using PySpark for processing large volumes of structured and unstructured data.
• Develop and manage ETL/ELT workflows using Informatica BDM.
• Work closely with data architects, analysts, and business stakeholders to understand data requirements and translate them into technical solutions.
• Optimize data processing jobs to ensure high performance and reliability.
• Implement data quality, data governance, and data validation processes.
• Integrate data from multiple sources including databases, APIs, and enterprise systems.
• Support data warehouse and data lake initiatives within the organization.
• Ensure compliance with banking regulatory and security standards.
• Troubleshoot and resolve data pipeline issues and performance bottlenecks.
• Participate in code reviews, testing, and deployment processes to maintain high development standards.

Required Skills & Qualifications

• 6+ years of experience in Data Engineering or related roles.
• Strong hands-on experience with PySpark for large-scale data processing.
• Solid experience with Informatica BDM (Big Data Management).
• Experience working with Big Data technologies and distributed data processing frameworks.
• Strong knowledge of SQL and data modeling concepts.
• Experience with data integration, ETL development, and workflow orchestration.
• Familiarity with cloud platforms or big data ecosystems (Hadoop/Spark environments) is a plus.
• Good understanding of data governance, security, and compliance requirements in banking.
• Domain Requirement: Mandatory experience in the Banking or Financial Services domain, preferably working with enterprise data platforms, regulatory reporting systems, or large-scale financial datasets.
• Preferred Qualifications: Experience with data lake architectures and data warehouse platforms. Exposure to Agile development methodologies. Knowledge of Python-based data engineering frameworks and automation.