Talend Architect

LTIMindtree is proud to be an equal opportunity employer. We are committed to equal employment opportunity regardless of race, ethnicity, nationality, gender, gender-identity, gender expression, language, age, sexual orientation, religion, marital status, veteran status, socio-economic status, disability or any other characteristic protected by applicable law.

Talend Architect

Experience: 12 to 22 years

Ghaziabad

Please share your updated resume – aditya.utekar2@ltimindtree.com

Primary Skill: ETL pipelines Design & Development Expertise; Talend ETL Dev & Admin; Real-Time Data Processing (Kafka); Big Data Frameworks (Hadoop, Spark); Metdata driven frameworks design.

Secondary Skills: Performance Tuning & Automation; Data Quality & Governance; API & Microservices Integration; Good Communication skills; Collaboration; Process Orietation; Troubleshooting skills; Continous learing.

The ETL Architect will design and implement real-time data integration solutions using Talend for the client platform. This role requires expertise in big data processing, ETL architecture, and cloud-based integration frameworks to ensure high performance, scalability, and compliance with government standards. The architect will lead ETL strategy, optimize data flows, and enable seamless interoperability across systems.

Key Responsibilities:

1. ETL Architecture & Design: Define and implement ETL architecture leveraging Talend for real-time and batch data processing. Design scalable, fault-tolerant data pipelines for ingestion, transformation, and loading into data lake/lakehouse environments. Establish best practices for ETL development, deployment, and monitoring.

2. Integration & Interoperability: Develop strategies for integrating heterogeneous data sources, APIs, and event-driven systems. Ensure compliance with government interoperability standards and security guidelines.

3. Performance Optimization: Optimize ETL workflows for high throughput, low latency, and efficient resource utilization. Implement automation for error handling, recovery, and performance tuning.

4. Collaboration & Leadership: Work closely with Data Architects, Solution Architects, and Data Engineers to align ETL design with overall architecture. Provide technical leadership and mentorship to ETL development teams.

5. Monitoring & Governance: Implement robust monitoring, logging, and alerting for ETL processes. Ensure adherence to data governance, quality, and security standards.

6. Innovation & Continuous Improvement: Stay updated with emerging ETL and big data technologies. Recommend innovative approaches to improve data integration and processing capabilities.

Regards,

Aditya Utekar

LTIMindtree