AI Data Engineer

Infosys; Bengaluru; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Infosys is seeking a data engineer to design and optimize production-grade ETL/ELT pipelines, curate datasets for analytics and GenAI workloads, and ensure data quality across sources. You will collaborate with cross-functional teams to implement data contracts and scalable data assets.

Ideal candidates have 3–5 years of data engineering experience, strong ETL skills, and exposure to GenAI-oriented data preparation.

Qualifications

• 3–5 years of experience in data engineering with ownership of production pipelines.
• Strong experience in ETL processes including extraction, transformation, orchestration, and scheduling.
• Exposure to GenAI oriented data preparation and AI/ML data workflows.

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 for accuracy, completeness, and reliability.
• Enable GenAI initiatives by preparing high-quality datasets for downstream consumption (e.g., feature-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.

Skills

SQL

Python

Apache Spark

Airflow

Data Modeling

Data Engineering

AI

Education

B.Tech / MTech / MCA / MSc or equivalent

Job description

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

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.

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.
• 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.