:

- About the job
- Join a team where data engineering meets intelligent automation to power next generation analytics and AI experiences
- In this role you ll help build reliable scalable data pipelines and enable GenAI ready datasets that support experimentation model development and business decision making
- You ll collaborate closely with analysts data scientists and platform teams to turn raw fragmented data into trusted well modeled and accessible assets
- If you enjoy solving complex data challenges improving performance and bringing structure to fast moving AI initiatives this is a great opportunity to grow your impact
- You ll work in a culture that values ownership continuous learning and practical innovation where clean data strong engineering and thoughtful collaboration come together to deliver real outcomes

Key Responsibilities:

- Key Responsibilities
- Design build and maintain robust ETL ELT pipelines to ingest transform and curate data from multiple sources
- Develop and optimize data models and curated datasets to support analytics reporting and AI ML workloads
- Implement data quality checks validation rules and monitoring to ensure accuracy completeness and reliability
- Enable GenAI initiatives by preparing high quality datasets for downstream consumption e
- g
- feature ready and retrieval ready data
- Collaborate with cross functional teams to gather requirements define data contracts and deliver reusable data assets




- Troubleshoot pipeline failures and performance bottlenecks improve scalability latency and cost efficiency
- Maintain documentation for pipelines transformations lineage and operational runbooks to support maintainability
- Minimum Qualifications
- BTECH MTECH MCA MSC or equivalent education
- 3 5 years of experience in data engineering with hands on ownership of production grade pipelines
- Strong experience in ETL processes including extraction transformation orchestration and scheduling
- Working exposure to GenAI oriented data preparation needs and supporting AI ML data workflows
- Ability to collaborate with stakeholders to translate requirements into scalable data solutions

Technical Requirements:

- Good to have skills
- SQL Python Apache Spark Airflow Data Modeling data engineering ai

Additional Responsibilities:

- Preferred Qualifications
- Experience designing scalable data architectures and implementing reusable data frameworks for multiple use cases
- Familiarity with building datasets for GenAI use cases such as retrieval workflows and knowledge augmentation patterns
- Proven ability to improve pipeline reliability through automation alerting and proactive monitoring
- Solid problem solving skills with a track record of optimizing transformations and reducing end to end processing time
- Experience working in agile teams and contributing to code reviews documentation and engineering best practices

Preferred Skills:

Technology->Data Engineering->Databricks,Technology->AI-Responsible AI->Responsible AI->explainable ai

📌 AI Data Engineer (Bengaluru)
🏢 Infosys
📍 Bengaluru