Usage of Conventional AI
Virtusa utilizes Artificial Intelligence (AI) technology for the purpose of conducting candidate pre-employment assessments. This AI may include both text-based and voice-based functionalities. The AI technology will have access to the data that you upload or provide during your interaction with the AI bot and will use such data solely for the purpose of performing assessment in accordance with Virtusa policies and practices. The AI is not used to substantially assist or replace discretionary employment decisions. Read our full employee privacy policy here.
Job description
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.
Strong analytical, problem-solving, and communication skills.
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.
Qualification
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.
Strong analytical, problem-solving, and communication skills.
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.
Key job details
About Virtusa
Teamwork, quality of life, professional and personal development: values that Virtusa is proud to embody. When you join us, you join a team of 30,000 people globally that cares about your growth — one that seeks to provide you with exciting projects, opportunities and work with state of the art technologies throughout your career with us.
Great minds, great potential: it all comes together at Virtusa. We value collaboration and the team environment of our company, and seek to provide great minds with a dynamic place to nurture new ideas and foster excellence.
Virtusa is an Equal Opportunity Employer. All applicants will receive fair and impartial treatment without regard to race, color, religion, sex, national origin, ancestry, age, legally protected physical or mental disability, protected veteran status, status in the U.S. uniformed services, sexual orientation, gender identity or expression, marital status, genetic information or on any other basis which is protected under applicable federal, state or local law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government-issued ID during each interview. All candidates must be authorized to work in the USA.
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