We are seeking an experienced Call Transcript Optimization Specialist to design, develop, and optimize data pipelines and processing frameworks supporting call transcription and conversational analytics. The candidate will work closely with solution architects, data engineering teams, and business stakeholders to build scalable data processing solutions that improve the quality, accuracy, accessibility, and usability of call transcript data.

The ideal candidate will have strong experience in cloud data engineering, AWS, Snowflake, ETL processes, and batch and near-real-time data processing, along with exposure to AI/ML, NLP, or GenAI-based solutions for conversational data analysis.

Required Technical Skills

- Experience: 7+ years in data engineering, cloud data platforms, data architecture, or related technical roles.
- AWS: Hands-on experience with AWS data services and cloud-based data processing architectures.
- Snowflake: Robust experience in Snowflake data warehousing, data processing, and performance optimization.
- ETL/ELT: Expertise in designing and implementing data extraction, transformation, and loading workflows.
- Data Pipelines: Experience developing scalable batch and near-real-time data pipelines.
- Programming: Proficiency in Python and SQL for data processing, transformation, and validation.
- Data Architecture: Experience with enterprise data lakes, data warehouses, and cloud migration initiatives.
- Data Quality: Understanding of data validation, monitoring, reconciliation,



and pipeline optimization.

Key Responsibilities

- Design, develop, and optimize scalable data pipelines to process call transcripts and associated conversational data.
- Build batch and near-real-time data processing solutions using AWS, Snowflake, and relevant cloud data services.
- Develop and maintain ETL/ELT workflows for data extraction, transformation, validation, and loading across enterprise platforms.
- Establish data processing frameworks to improve transcript data quality, consistency, completeness, and accessibility.
- Collaborate with solution architects and business stakeholders to understand requirements and translate them into scalable technical solutions.
- Support the integration of call transcript data with enterprise data lakes, data warehouses, and downstream analytics platforms.
- Identify opportunities to optimize data processing performance, pipeline reliability, scalability, and operational efficiency.
- Work with AI/ML and NLP teams to enable transcript analysis, conversational insights, text processing, and automated quality improvement.
- Implement data validation, monitoring, error handling, and quality assurance mechanisms across data pipelines.
- Lead technical discussions, contribute to solution design, and collaborate with cross-functional teams to deliver projects within agreed timelines.
- Follow Agile delivery practices and ensure adherence to enterprise architecture, security, and data governance standards.

📌 Data Architect (Bengaluru)
🏢 InfoVision
📍 Bengaluru