Job DescriptionAbout the job

Join a team where data engineering meets intelligent automation to power next-generation analytics and AI experiences. In this role, youll help build reliable, scalable data pipelines and enable GenAI-ready datasets that support experimentation, model development, and business decision-making. Youll 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 quick-moving AI initiatives, this is a great opportunity to grow your impact. Youll work in a culture that values ownership, continuous learning, and practical innovationwhere clean data, strong engineering, and thoughtful collaboration come together to deliver real outcomes.

Roles ResponsibilitiesKey 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.

- 35 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 RequirementGood to have skills:

SQL, Python, Apache Spark, Airflow, Data Modeling, data engineering, ai

Additional ResponsibilityPreferred 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.

- Strong 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.

Educational RequirementMCA,MSc,MTech,Bachelor of Engineering,BTech

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

Service LineData Analytics Unit

📌 AI Data Engineer (Bengaluru)
🏢 Infosys
📍 Bengaluru