Key Responsibilities
Data Architecture & Design
- Contribute to the design of scalable, agile, and robust data architecture solutions
- Develop enterprise data models and information infrastructure across business domains
- Define how data flows across systems such as CRM, Finance, HR, and Sales platforms
- Design data persistence solutions using relational and non-relational databases
Data Pipeline Development & Engineering
- Build and maintain data pipelines from internal and external data sources
- Develop systems for data ingestion, cleansing, transformation, and normalization
- Handle structured and unstructured data using modern data engineering practices
- Implement event-driven and streaming-based data pipelines
Master Data Management (MDM) & Data Governance
- Design and implement MDM strategies using Informatica MDM suite
- Develop and support metadata management, data quality, and governance frameworks
- Ensure consistency, accuracy, and integrity of enterprise master data
- Support compliance with data governance policies and standards
Cloud & Platform Engineering
- Develop solutions using cloud platforms such as Azure and AWS
- Work with data lakes, distributed systems, and cloud-native architectures
- Implement microservices, streaming technologies, and scalable data systems
- Enhance data processing capabilities using modern cloud tools
Data Integration & Advanced Analytics Support
- Integrate data from multiple enterprise systems and external sources
- Support analytics and reporting through high-quality, well-structured datasets
- Build reusable data assets for business intelligence and machine learning use cases
- Develop proofs of concept (POCs) to validate architecture and solution approaches
Technical Leadership & Mentoring
- Provide functional leadership to a team of data engineers in Agile environments
- Mentor junior engineers and guide best practices in data engineering
- Support cross-functional collaboration with architects, product managers, and software engineers
- Ensure timely delivery of data solutions with high quality standards
Operations & Continuous Improvement
- Monitor and optimize performance of data pipelines and storage systems
- Troubleshoot and resolve data-related issues in production environments
- Continuously improve data architecture and engineering practices
- Ensure reliability, scalability, and efficiency of data platforms
